<?xml version="1.0" encoding="UTF-8"?><WFS_Capabilities version="1.0.0" xmlns="http://www.opengis.net/wfs" xmlns:geonode="http://www.geonode.org/" xmlns:ogc="http://www.opengis.net/ogc" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.opengis.net/wfs https://crd.resilienceacademy.ac.tz/geoserver/schemas/wfs/1.0.0/WFS-capabilities.xsd"><Service><Name>My GeoServer WFS</Name><Title>My GeoServer WFS</Title><Abstract>This is a description of your Web Feature Server.&#13;
&#13;
The GeoServer is a full transactional Web Feature Server, you may wish to limit&#13;
GeoServer to a Basic service level to prevent modificaiton of your geographic&#13;
data.</Abstract><Keywords>WFS, WMS, GEOSERVER</Keywords><OnlineResource>http://geoserver.sourceforge.net/html/index.php</OnlineResource><Fees>NONE</Fees><AccessConstraints>NONE</AccessConstraints></Service><Capability><Request><GetCapabilities><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=GetCapabilities"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></GetCapabilities><DescribeFeatureType><SchemaDescriptionLanguage><XMLSCHEMA/></SchemaDescriptionLanguage><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=DescribeFeatureType"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></DescribeFeatureType><GetFeature><ResultFormat><GML2/><GML3/><SHAPE-ZIP/><CSV/><JSONP/><JSON/><KML/></ResultFormat><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=GetFeature"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></GetFeature><Transaction><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=Transaction"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></Transaction><LockFeature><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=LockFeature"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></LockFeature><GetFeatureWithLock><ResultFormat><GML2/></ResultFormat><DCPType><HTTP><Get onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs?request=GetFeatureWithLock"/></HTTP></DCPType><DCPType><HTTP><Post onlineResource="https://crd.resilienceacademy.ac.tz/geoserver/wfs"/></HTTP></DCPType></GetFeatureWithLock></Request></Capability><FeatureTypeList><Operations><Query/><Insert/><Update/><Delete/><Lock/></Operations><FeatureType><Name>geonode:dar_urban_greening_project_openspaces31aae75a18d3</Name><Title>Dar Urban Greening Project - AOIs</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>AOI, dar_urban_greening_project_openspaces31aae75a18d3, urban greening, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.161123" miny="-6.932206391" maxx="39.35060129" maxy="-6.752457487"/></FeatureType><FeatureType><Name>geonode:urban_green_2022_boreholes</Name><Title>Dar Urban Greening Project - Boreholes</Title><Abstract>Urban green boreholes were collected using a survey by 20 university students who collaborated with community members to collect data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>urban_green_2022_boreholes, urban greening, boreholes, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.16131042" miny="-6.93095297" maxx="39.25613219" maxy="-6.755708404"/></FeatureType><FeatureType><Name>geonode:urban_greening_buildings_polygon</Name><Title>Dar Urban Greening Project - Building polygons</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>buildings, urban greening, urban_greening_buildings_polygon, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.16110729777671" miny="-6.932778394468582" maxx="39.3510236977032" maxy="-6.752047594688185"/></FeatureType><FeatureType><Name>geonode:urban_greening_highways</Name><Title>Dar Urban Greening Project - Highways</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>highways, urban greening, urban_greening_highways, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1607725" miny="-6.932762874405568" maxx="39.351003247950324" maxy="-6.7519266"/></FeatureType><FeatureType><Name>geonode:urban_green_2022_natural_drainagegpkg_wal</Name><Title>Dar Urban Greening Project - Natural drainage</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>urban_green_2022_natural_drainagegpkg_wal, natural drainage, urban greening, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.23892187220915" miny="-6.840754603047223" maxx="39.24227625131607" maxy="-6.839748445611456"/></FeatureType><FeatureType><Name>geonode:dar_urban_greening_project_openspaces</Name><Title>Dar Urban Greening Project - Open spaces</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>features, urban greening, dar_urban_greening_project_openspaces, open spaces</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.161123" miny="-6.932206391" maxx="39.35060129" maxy="-6.752457487"/></FeatureType><FeatureType><Name>geonode:dar_urban_greening_project_solid_waste</Name><Title>Dar Urban Greening Project - Solid waste</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>solid waste, urban greening, features, dar_urban_greening_project_solid_waste</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1652154" miny="-6.8494171" maxx="39.23938944" maxy="-6.754483819"/></FeatureType><FeatureType><Name>geonode:dar_urban_greening_project_openspacese4a5e33a6984</Name><Title>Dar Urban Greening Project - Tributaries</Title><Abstract>The survey was conducted by 20 university students who collaborated with community members to collect this data sets. Data collection covered 15 sampled areas in Dar es salaam city, representing six settlement characteristics i.e residential (planned and unplanned), Planned and unplanned residential were further divided into high, medium, and low population density categories.</Abstract><Keywords>features, dar_urban_greening_project_openspacese4a5e33a6984</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.161123" miny="-6.932206391" maxx="39.35060129" maxy="-6.752457487"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_administrative_districts</Name><Title>Dar es Salaam Administrative Districts</Title><Abstract>Districts/municipalities of Dar es Salaam. Districts corresponds to administrative level 2 in the Global Administrative database (GADM). Districts covers a certain number of households, which means the number of districts increase when the population of certain area increases. Currently there are five (5) districts in the region of Dar es Salaam, listed from west to east: Kinondoni, Ubungo, Ilala, Temeke and Kigamboni. The most recent districts - Ubungo and Kigamboni - were established in 2016 due to population increase. This data set is originated from the Tanzania National Bureau of Statistics and is shared in Climate Risk Database for reference purposes. Download full data set of districts in Tanzania from: https://www.nbs.go.tz/index.php/en/census-surveys/gis/568-tanzania-districts-shapefiles-2019.</Abstract><Keywords>dar_es_salaam_administrative_districts, administrative boundaries, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0071592382959" miny="-7.181490835157371" maxx="39.55376584046384" maxy="-6.56620696403837"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_administrative_region</Name><Title>Dar es Salaam Administrative Region</Title><Abstract>Administrative boundaries of the Dar es Salaam region. Region corresponds to administrative level 1 in the Global Administrative database (GADM). This layer has been produced by Tanzania National Bureau of Statistics.</Abstract><Keywords>administrative, dar_es_salaam_administrative_region, features, border</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0071592382959" miny="-7.181490838157122" maxx="39.553765922465416" maxy="-6.566206931041475"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_administrative_subwards</Name><Title>Dar es Salaam Administrative Sub-wards</Title><Abstract>Sub-wards (Mtaa in Swahii) in Dar es Salaam are small administrative areas. There are now 478 sub-wards in Dar es Salaam. Ramani Huria team mapped and added the 15 newest sub-wards to this data set. Sub-wards corresponds to administrative level 4 in Global Administrative database (GADM).</Abstract><Keywords>features, dar_es_salaam_administrative_subwards, administrative boundaries</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0071592382959" miny="-7.181490838157123" maxx="39.553765922465416" maxy="-6.566206931041475"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_administrative_wards715f5b45aeaf</Name><Title>Dar es Salaam Administrative Wards</Title><Abstract>Wards (Kata in Swahili) are administrative regions in Dar es Salaam. Wards corresponds to administrative level 3 in Global Administrative (GADM) database of high-resolution administrative areas. Original data is provided by the Tanzania National Bureau of Statistics from the year 2012. Five new wards of Bonyokwa, Kisukuru, Liwiti, Mnyamani and Pugu Station were mapped by the Ramani Huria team and added to this data set in 2018.</Abstract><Keywords>features, dar_es_salaam_administrative_wards715f5b45aeaf, administrative boundaries</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.00715923800004" miny="-7.181490837999945" maxx="39.553765922000025" maxy="-6.566206930999954"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_brt_routes_039f2af0d5edcdad6c1811f21165f4ad</Name><Title>Dar es Salaam BRT Route (Phase 1)</Title><Abstract>This dataset contains the Bus Rapid Transit route (phase 1) of Dar es Salaam. The Dar Rapid Transit (DART) is a mass transit system that connects the suburbs to the central business district. This dataset was collected by the Ramani Huria team in year 2018. Note: the dataset of BRT stops is also downloadable from Climate Risk Database.</Abstract><Keywords>DART, features, Bus Rapid Transit, dar_es_salaam_brt_routes_039f2af0d5edcdad6c1811f21165f4ad, BRT, public transportation</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.183274" miny="-6.8264308" maxx="39.2989248" maxy="-6.7774908"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_brt_stops</Name><Title>Dar es Salaam BRT Stops (Phase I)</Title><Abstract>This dataset contains the 34 stops of Bus Rapid Transit route in the city of Dar es Salaam. The major stops are Jangwani, Kimara, Morocco, Gerezani, and Kivukoni. This dataset was collected by Ramani Huria team in the year 2018. Note: the dataset of BRT route is also downloadable from Climate Risk Database.</Abstract><Keywords>DART, public transportation, features, dar_es_salaam_brt_stops, BRT, Bus Rapid Transit</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1866543" miny="-6.8261894" maxx="39.2986187" maxy="-6.7777287"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_business_areas</Name><Title>Dar es Salaam Business Areas</Title><Abstract>Areas in Dar es Salaam whose predominant feature is commercial purposes including offices, social facilities, financial services such as banks, atm, bureau de change, mobile money, etc.</Abstract><Keywords>tourism, features, office, amenity, dar_es_salaam_business_areas, shop</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0547113" miny="-6.9351003" maxx="39.3508568" maxy="-6.6406581"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_business_locations</Name><Title>Dar es Salaam Business Locations</Title><Abstract>Areas in Dar es Salaam whose predominant feature is commercial purposes including offices, social facilities, financial services such as banks, atm, bureau de change, mobile money, etc.</Abstract><Keywords>dar_es_salaam_business_locations, tourism, office, amenity, features, shop</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1215932" miny="-6.9011741" maxx="39.2811657" maxy="-6.7043433"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_catchments</Name><Title>Dar es Salaam Catchments</Title><Abstract>River catchments in Dar es Salaam generated from the HYDROSheds dataset (3 second conditioned DEM) https://hydrosheds.cr.usgs.gov/ . Used for the Msimbazi Charrette project.</Abstract><Keywords>catchments, features, hydrology, watershed, dar_es_salaam_catchments</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.987418958000035" miny="-6.97219682399998" maxx="39.28158562400006" maxy="-6.723863490999975"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_drain_points</Name><Title>Dar es Salaam Drainage Points</Title><Abstract>Drainage data of 31 out of 44 wards of the city (ongoing process). Drain points and segments traced by using ODK Collect application.</Abstract><Keywords>drain, flood, Drainage, features, dar_es_salaam_drain_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.11234038626353" miny="-6.896984588639111" maxx="39.28666" maxy="-6.624401888812985"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_drain_segments</Name><Title>Dar es Salaam Drainage Segments</Title><Abstract>Drainage data of 31 out of 44 wards of the city (ongoing process). Drain points and segments traced by using ODK Collect application.</Abstract><Keywords>drain, flood, Drainage, dar_es_salaam_drain_segments, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.11234038626353" miny="-6.896984588639111" maxx="39.286665" maxy="-6.624401888812985"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_education_facilities_locations0</Name><Title>Dar es Salaam Education Facilities' Locations</Title><Abstract>Educational facilities in Dar es Salaam including kindergarten, primary and secondary school, college and universities that provide education services.</Abstract><Keywords>education, university, kindergarten, features, school, amenities, dar_es_salaam_education_facilities_locations0, exposure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0671911" miny="-6.940259" maxx="39.3163149" maxy="-6.6336846"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_flood_scenario_25___200_cm</Name><Title>Dar es Salaam Flood Scenario_ 25-200 cm</Title><Abstract>This layer represents flood scenario for 25 to 200 centimeters in the Dar es Salaam region. Flood scenario has been produced from the Dar es Salaam Digital Terrain Model, 5cm 2017, and thus it's accuracy is dependent on the quality of that DTM dataset. The scenario covers the shoreline, too, but since river flooding is the main cause of flooding in Dar es Salaam, the coastline scenarios are irrelevant. This dataset was created by the winning group of 2020 Visualisation challenge in University of Turku.</Abstract><Keywords>flood scenario, features, dar_es_salaam_flood_scenario_25___200_cm, winner, UTU, visualisation challenge</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.09579089862734" miny="-6.9625124436592065" maxx="39.47459660263135" maxy="-6.598532547701874"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_government_polygon</Name><Title>Dar es Salaam Government Offices</Title><Abstract>Offices that are operated by the government including national, regional or local government agency or department in Dar es Salaam which can be used to indicate all branches of government i.e. executive, legislative, and judiciary carrying out tasks such as administering facilities, operate registries and licensing bureaus, regulate lands and/or people, etc.</Abstract><Keywords>features, dar_es_salaam_government_polygon</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1030007" miny="-6.9142865" maxx="39.3001779" maxy="-6.7430103"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_government_points</Name><Title>Dar es Salaam Government Offices' Locations</Title><Abstract>Offices that are operated by the government including national, regional or local government agency or department in Dar es Salaam which can be used to indicate all branches of government i.e. executive, legislative, and judiciary carrying out tasks such as administering facilities, operate registries and licensing bureaus, regulate lands and/or people, etc.</Abstract><Keywords>features, dar_es_salaam_government_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0728248" miny="-6.9142606" maxx="39.2983598" maxy="-6.6609069"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_historical_flood_depths</Name><Title>Dar es Salaam Historical Flood Depths</Title><Abstract>This dataset comprises of flood depth history experienced by the local people living in Dar es Salaam's most flood-prone areas during rainy seasons. More specifically, the local residents were surveyed in eleven wards located nearby the Msimbazi river and river streams. Historical records consists of the years of flood occurence, flood depth, reasons for flooding, types of buildings affected and whether residents moved from the area or not. The aim was to collect a comprehensive data set about people's experiences and whether they were affected by floodings in previous years or not. Data was collected by Ramani Huria project, hosted by Humanitarian OpenStreetMap Team (HOT). Local residents were interviewed with a structured survey and their answers were recorded with the coordinate information of their homes. ODK Collect toolkit was used as the collection tool.</Abstract><Keywords>dar_es_salaam_historical_flood_depths, flood experience, hazard, flood depth, flood, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.23142273" miny="-6.8351383" maxx="39.27407872" maxy="-6.7907416667"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_historical_flood_extent</Name><Title>Dar es Salaam Historical Flood Extent</Title><Abstract>The dataset comprises of flood history (years of flood occurence), flood depth, reasons for flooding, types of buildings, uses, whether residents were evacuated or not. All data points were collected by using ODK Collect.</Abstract><Keywords>Flood history, flood experience, dar_es_salaam_historical_flood_extent, hazard, flood depth, Flood extent, Flood mitigation, survey, flood, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.23025374" miny="-6.83811" maxx="39.28173" maxy="-6.7818033333"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_hospital_polygon</Name><Title>Dar es Salaam Hospitals</Title><Abstract>Health care institutions in Dar es Salaam providing in-patient medical treatment by specialised staff and equipment, and typically providing nursing care for longer-term patient stays.</Abstract><Keywords>dispensing, features, emergency, amenities, dar_es_salaam_hospital_polygon, ancillary, health care</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1182756" miny="-6.9034149" maxx="39.2888625" maxy="-6.7281369"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_hospital_points</Name><Title>Dar es Salaam Hospitals' Locations</Title><Abstract>Health care institutions in Dar es Salaam providing in-patient medical treatment by specialised staff and equipment, and typically providing nursing care for longer-term patient stays.</Abstract><Keywords>dar_es_salaam_hospital_points, medicine, amenities, pharmacies, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0854073" miny="-6.9142791" maxx="39.2961939" maxy="-6.6530096"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_hydro_met_stations</Name><Title>Dar es Salaam Hydro-Met Stations</Title><Abstract>This layer contains the locations of hydro-meteorological TAHMO stations (ATMOS-41), Sommer RQ-30 Sensor and Ijinus Ultra-SonicWater level Sensors in Tanzania. Each station collects data at 5min resolution/month for twelve parameters (including: rainfall, wind speed, wind gusts, wind direction, solar radiation, atmospheric pressure, temperature, and relative humidity). This dataset only provides the station locations and date of first measurement. The data itself is free to use in research purposes, and can be accessed through the dashboard: https://portal.tahmo.org/portal/map. Accessing the data requires Gmail registration via emailing info@tahmo.fi - see FAQ on the TAHMO webpage: https://tahmo.org/.</Abstract><Keywords>features, dar_es_salaam_hydro_met_stations</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.747035" miny="-6.9107633" maxx="39.2661084" maxy="-2.43833"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_hyperlocal_boundaries</Name><Title>Dar es Salaam Hyperlocal Boundaries</Title><Abstract>Detailed hyperlocal boundary mapping (the most granular administrative level in Tanzania) in 31 wards of the city by tracing polygons using ODK Collect application. Hyperlocal boundaries are divisions within subwards regarded as political boundaries previously referred to as ten cell divisions as they were originally comprised of ten households. Due to the increase in population, they comprise of 30 to 200 households and are administered by local leaders (wajumbe). Wajumbe are increasingly functioning as non-partisan public servants, often the first━in most cases━point of interaction between the government and citizens. The data can be used to easily reach or access people's addresses.</Abstract><Keywords>administrative areas, Hyperlocal boundaries, dar_es_salaam_hyperlocal_boundaries, features, 'shinas', 'mjumbe'</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.08807736961261" miny="-6.961210707236279" maxx="39.30070990521081" maxy="-6.765797552988738"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_hyperlocal_boundaries174899b7e91f</Name><Title>Dar es Salaam Hyperlocal Boundaries</Title><Abstract>Detailed hyperlocal boundary mapping (the most granular administrative level in Tanzania) in 31 wards of the city by tracing polygons using ODK Collect application. Hyperlocal boundaries are divisions within subwards regarded as political boundaries previously referred to as ten cell divisions as they were originally comprised of ten households. Due to the increase in population, they comprise of 30 to 200 households and are administered by local leaders (wajumbe). Wajumbe are increasingly functioning as non-partisan public servants, often the first━in most cases━point of interaction between the government and citizens. The data can be used to easily reach or access people's addresses.</Abstract><Keywords>'shinas', 'mjumbe', Hyperlocal boundaries, features, administrative areas, dar_es_salaam_hyperlocal_boundaries174899b7e91f</Keywords><SRS>EPSG:3857</SRS><LatLongBoundingBox minx="39.088077369851966" miny="-6.961210707380182" maxx="39.30070990555009" maxy="-6.765797552968433"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_inundated_buildings</Name><Title>Dar es Salaam Inundated Buildings</Title><Abstract>Inundation data of several Wards in Dar es Salaam, collected by the Ramani Huria project. Data represents experiences of local inhabitants who were interviewed whether their residence had been inundated or not. The inundation records are from multiple different flooding events over several years. Critical facilities have been mapped, too.</Abstract><Keywords>flood experience, flooding, features, inundation, dar_es_salaam_inundated_buildings</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.18929059784765" miny="-6.865699895020131" maxx="39.288261397855" maxy="-6.732785095132051"/></FeatureType><FeatureType><Name>geonode:dar_landuselandcover</Name><Title>Dar es Salaam Land Use/Land Cover_ 2010</Title><Abstract>Land use and land cover map of Dar es Salaam from the year 2010.</Abstract><Keywords>features, land cover, dar_landuselandcover, land use</Keywords><SRS>EPSG:6210</SRS><LatLongBoundingBox minx="-49.48839442739898" miny="-6.475390795251861E-5" maxx="-49.48838953045108" maxy="-5.920390774207731E-5"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_river_channels</Name><Title>Dar es Salaam Main River Channels</Title><Abstract>The dataset was derived from the digital terrrain model (DTM) produced by COWI. The process involved classification of the flow accumulation grid derived from the DTM using ArcHydro tools in ArcGIS. The raster dataset has been converted into a vector layer. Layer only display the mian watercouses after the small modelled watercouses were filter out. By JBA Consulting.</Abstract><Keywords>dar_es_salaam_river_channels, features, geomorphology, environment, river channels</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="38.95097646408514" miny="-7.1883890881257475" maxx="39.54688140364401" maxy="-6.568080408448569"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_office_points</Name><Title>Dar es Salaam Non-governmental Office's Locations</Title><Abstract>Areas in Dar es Salaam that predominatly provide services, frequently selling them ranging from obvious services such as accountants and lawyers to forestry or NGO office.</Abstract><Keywords>features, dar_es_salaam_office_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0728248" miny="-6.9154114" maxx="39.3118378" maxy="-6.6609069"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_office_polygons</Name><Title>Dar es Salaam Non-governmental Offices</Title><Abstract>Areas in Dar es Salaam that predominatly provide services, frequently selling them ranging from obvious services such as accountants and lawyers to forestry or NGO office.</Abstract><Keywords>features, dar_es_salaam_office_polygons</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.097757" miny="-6.9142865" maxx="39.3001779" maxy="-6.7430103"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_open_areas</Name><Title>Dar es Salaam Open Areas</Title><Abstract>Dar es Salaam Open Areas layer contains polygons of undeveloped pieces of land in Dar es Salaam including brownfields, cemetery, dump, farmland, farmyard, forest, grass, greenfield, meadow, wetland etc. but are accessible to the public. This data set has been collected during the Ramani Huria project in Dar es Salaam. Features of the data set follows OpenStreetMap guidelines (https://wiki.openstreetmap.org/wiki/Landuse).</Abstract><Keywords>dar_es_salaam_open_areas, features, open areas, land use</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1035304" miny="-6.9996074" maxx="39.5243562" maxy="-6.6596075"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_pharmacy</Name><Title>Dar es Salaam Pharmacies</Title><Abstract>Shops in Dar es Salaam also referred to as drugstores that sell medications as regulated and licensed by the government.</Abstract><Keywords>dispensing, dar_es_salaam_pharmacy, ancillary, amenities, emergency, features, health care</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0619936" miny="-6.9174124" maxx="39.2954718" maxy="-6.6615593"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_public_toilets_polygon</Name><Title>Dar es Salaam Public Toilets</Title><Abstract>Toilets in Dar es Salaam provided and maintained by the public authorities available for the general public to use usually should be suitable to be used with a wheelchair and a person with a disability who uses another mobility device (like a walker).</Abstract><Keywords>features, dar_es_salaam_public_toilets_polygon</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0888066" miny="-6.8982464" maxx="39.2860373" maxy="-6.7613156"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_public_toilets_points</Name><Title>Dar es Salaam Public Toilets' Locations</Title><Abstract>Toilets in Dar es Salaam provided and maintained by the public authorities available for the general public to use usually should be suitable to be used with a wheelchair and a person with a disability who uses another mobility device (like a walker).</Abstract><Keywords>features, dar_es_salaam_public_toilets_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1911847" miny="-6.9407411" maxx="39.5051137" maxy="-6.6946697"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_public_transportation_routes</Name><Title>Dar es Salaam Public Transportation Routes</Title><Abstract>This dataset contains routes of public transportation (dala dala) routes in Dar es Salaam.</Abstract><Keywords>bus routes, dar_es_salaam_public_transportation_routes, public transportation, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.04697107581713" miny="-7.030666754804557" maxx="39.45569682866766" maxy="-6.577853136993972"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_public_transportation_stops</Name><Title>Dar es Salaam Public Transportation Stops</Title><Abstract>This dataset contains bus stops along the Dar es Salaam public transportation route. Dataset covers 49 wards (out of 95) in Dar es Salaam and it was collected by Ramani Huria team. Stops were uploaded to OpenStreetMap as well. Note: the dataset of public transportation route is also downloadable from Climate Risk Database.</Abstract><Keywords>Bus stops, dar_es_salaam_public_transportation_stops, public transportation, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1320713" miny="-6.8866156" maxx="39.3767934" maxy="-6.7007798"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_public_water_points</Name><Title>Dar es Salaam Public Water Points</Title><Abstract>Public water points in Dar es Salaam where one can obtain potable water for consumption including water taps, water wells and water points that are accessed by the general public</Abstract><Keywords>pump, dar_es_salaam_public_water_points, features, drinking water, public water, amenity</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.1156268" miny="-6.9148815" maxx="39.2882895" maxy="-6.7680554"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_religious_institution_polygon</Name><Title>Dar es Salaam Religious Services Facilities</Title><Abstract>Places of worship in Dar es Salaam covering assortments of community facilities such as churches, mosque, temples and confession schools. The religious institutions are classified according to religion that is Christian, Muslim, Buddha etc. they are further classified according to their denominations such as Roman Catholic, Pentecostal, Lutheran, Anglican, Shia, Sunni etc.</Abstract><Keywords>denomination, features, religion, dar_es_salaam_religious_institution_polygon, mosque, church, temple, amenity</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0648846" miny="-6.9400553" maxx="39.3316169" maxy="-6.6427373"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_religious_institution_pointsdd77e5cf868c</Name><Title>Dar es Salaam Religious Services Facilities' Locations</Title><Abstract>Places of worship in Dar es Salaam covering assortments of community facilities such as churches, mosque, temples and confession schools. The religious institutions are classified according to religion that is Christian, Muslim, Buddha etc. they are further classified according to their denominations such as Roman Catholic, Pentecostal, Lutheran, Anglican, Shia, Sunni etc.</Abstract><Keywords>amenity, temple, features, mosque, religion, church, denomination, dar_es_salaam_religious_institution_pointsdd77e5cf868c</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0226415" miny="-6.9711476" maxx="39.3113148" maxy="-6.6516709"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_shops_polygon</Name><Title>Dar es Salaam Retail Services</Title><Abstract>Areas selling retail products in Dar es Salaam which may range from the obvious shops such as supermarkets and places to buy food to video rental and car dealerships and to places offering some kind of retail service such as paying electricity bills, high street solicitors or travel agencies.</Abstract><Keywords>retail, dar_es_salaam_shops_polygon, shops, amenity, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0547113" miny="-6.9328625" maxx="39.2929948" maxy="-6.7091983"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_education_facilities_locations01563b83e4182</Name><Title>Dar es Salaam Retail Services' Locations</Title><Abstract>Areas selling retail products in Dar es Salaam which may range from the obvious shops such as supermarkets and places to buy food to video rental and car dealerships and to places offering some kind of retail service such as paying electricity bills, high street solicitors or travel agencies. Shops are commercial areas that provide different services. They may include hairdresser, kiosk, bakery, green grocer, convenience store, stationery, etc.</Abstract><Keywords>dar_es_salaam_education_facilities_locations01563b83e4182, retail, amenity, features, shop</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0671911" miny="-6.940259" maxx="39.3163149" maxy="-6.6336846"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_river_basins</Name><Title>Dar es Salaam River Basins</Title><Abstract>The dataset was derived from the digital terrrain model (DTM) produced by COWI. The process involved classification of the flow accumulation grid derived from the DTM using ArcHydro tools in ArcGIS. The raster dataset has been converted into a vector layer. By JBA Consulting.</Abstract><Keywords>features, dar_es_salaam_river_basins</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="38.93238375884063" miny="-7.2036778738213885" maxx="39.55179067102961" maxy="-6.549079072168119"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_rivers</Name><Title>Dar es Salaam Rivers</Title><Abstract>Rivers in Dar es Salaam were delineated based on catchment analyses and corrected using Google Earth imagery. Used for the Msimbazi Charrette project.</Abstract><Keywords>features, dar_es_salaam_rivers</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.008668958000044" miny="-6.94886349099994" maxx="39.28158562400006" maxy="-6.72678015799994"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_roads_442d5ed5bfa4522c77d3303f1a2ddef8</Name><Title>Dar es Salaam Roads</Title><Abstract>Highway data of all the roads in Dar es Salaam classified according to trunk, primary, secondary, tertiary, residential, unclassified and footpath with names (formal and informal) and width. This data set is originated from OpenStreetMap database, curated and modified by HOT. *** NOTE: The whole data set is large, we recommend downloading only parts of it, if possible.</Abstract><Keywords>highway, streets, features, roadnetwork, road, dar_es_salaam_roads_442d5ed5bfa4522c77d3303f1a2ddef8, paths</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.9708168" miny="-7.4038922" maxx="39.5507216" maxy="-6.5755392"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_roads</Name><Title>Dar es Salaam Roads 2022</Title><Abstract>The data was collected to provide updates on all roads in Dar es Salaam for 2022.</Abstract><Keywords>dar_es_salaam_roads, roads, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.9708168" miny="-7.4038922" maxx="39.5507216" maxy="-6.5755392"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_soil_sediment_sampling</Name><Title>Dar es Salaam Soil Classes</Title><Abstract>The dataset is based on 731 soil sample points created in ArcGIS using a 2km by 2km regular grid on the whole of Dar es Salaam's catchment area. Each sample point with a unique code to identify it. The surface soil dataset for the greater Dar es Salaam region of Tanzania. This was intended to support a geomorphological assessment taking into account soil characteristics for erosion and flood risk studies. A national-level soil profile had existed for Tanzania prior to this effort, but contained only a single sample from Dar es Salaam. This was not sufficient to analyse erosion potential across the city. A 2km grid was used which resulted in 731 sampling points being pre-established throughout the city.</Abstract><Keywords>Soil sampling, dar_es_salaam_soil_sediment_sampling, flood risks, soil, sieving, features, geomorphological assessment, catchment area</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.91432" miny="-7.19723" maxx="39.5450133333" maxy="-6.5583533333"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_tourism_points</Name><Title>Dar es Salaam Tourist Attractions' Locations</Title><Abstract>Areas in Dar es Salaam that provide information and support to tourists. These include hotel, motel, guest house, hostel, museum, campsite, gallery, picnic site and view points.</Abstract><Keywords>features, dar_es_salaam_tourism_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.0406632" miny="-7.016678" maxx="39.5475482" maxy="-6.6549451"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_tree_mapping</Name><Title>Dar es Salaam Tree Mapping</Title><Abstract>This dataset was collected by University students from UDSM and ARU during the Resilience Academy Industrial Training 2020 period. Mapping was overseen by OMDTZ and Greenstand.</Abstract><Keywords>environment, dar_es_salaam_tree_mapping, natural, trees, tree species, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.20992666666667" miny="-6.81" maxx="39.27" maxy="-6.78595014"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_tree_mapping_pilot</Name><Title>Dar es Salaam Tree Mapping Pilot</Title><Abstract>This data set contains 556 mapped trees in the area of Mikocheni ward in Dar es Salaam. Points representing trees has attribute values of e.g. tree species, tree health and type of threath threathening the tree. This data set is a pilot mapping project where an efficient and high-quality metodology for mapping urban trees was created and tested. In later phases of the project mapping of the trees is broadened to a subward level in Dar es Salaam. The project is conducted by the World Bank, OpenMap Development Tanzania (OMDTZ) and Greenstand.</Abstract><Keywords>features, dar_es_salaam_tree_mapping_pilot</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.25206974" miny="-6.778695" maxx="39.26443167" maxy="-6.763203333"/></FeatureType><FeatureType><Name>geonode:dar_es_salaam_waste_sites</Name><Title>Dar es Salaam Waste Sites</Title><Abstract>Data points of areas with poorly managed solid waste. The map includes the size of waste material, type of waste material and suggested cleanup methods.</Abstract><Keywords>trash, environment, features, trash size, EPSG:4326, solid waste, dar_es_salaam_waste_sites</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.043721" miny="-6.93686674" maxx="39.3253351714691" maxy="-6.62841535714286"/></FeatureType><FeatureType><Name>geonode:existing_building_as_received_from_client</Name><Title>Existing Building As Received From Client</Title><Abstract>Existing Building As Received from Client dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Existing, features, from, buildings, As, existing_building_as_received_from_client, Received, Client</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.862181012853874" miny="-2.648292113282301" maxx="33.03082447200341" maxy="-2.4409745729351267"/></FeatureType><FeatureType><Name>geonode:existing_water_supply_pump_stationd5e5250fc378</Name><Title>Existing Water Supply Pump Station</Title><Abstract>Existing Water Supply Pump Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Pump, features, Station, water, Supply, existing_water_supply_pump_stationd5e5250fc378, Existing</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.88576127973253" miny="-2.5853461552151176" maxx="33.02836332699394" maxy="-2.4882633229411684"/></FeatureType><FeatureType><Name>geonode:kahama_drain_points</Name><Title>Kahama Drainage Points</Title><Abstract>This dataset will contains information about locations of drain points of interest in Kahama. These points will identify various features found within drainage system such as blockages, damaged points, exits, outflows, and others. This dataset will be produced under the Tanzania Urban Resilience Program in Kahama and Kigoma The assignment shall build on previous knowledge of community mapping and open-source digital spatial data collection acquainted with TURP, and in doing so build digital skills and create job opportunities for the students. This dataset will cover Kahama Mjini, Majengo and parts of the Malunga, Nyahanga, Nyihogo, Nyasubi and Mhongolo in Kahama .</Abstract><Keywords>Drainage, features, kahama_drain_points, Urban Infranstructure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.57156987" miny="-3.856211262130192" maxx="32.63436944607989" maxy="-3.787178434723452"/></FeatureType><FeatureType><Name>geonode:kigoma_elevation_points_c8f6a83c02e171fc81f0c9a6014dc5f0</Name><Title>Kahama Drainage Points Elevations</Title><Abstract>This dataset will contains information about locations of drain points of interest in Kahama and Kigoma. These points will identify various features found within drainage system such as blockagees, damaged points, exit, outflow and others. This dataset will be produced under the Tanzania Urban Resilience Program in Kahama and Kigoma The assignment shall build on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students. This dataset will cover Kahama Mjini, Majengo and parts of the Malunga, Nyahanga, Nyihogo, Nyasubi and Mhongolo in Kahama</Abstract><Keywords>elevation, features, Drainage, EPSG:4326, urban infrastructure, kigoma_elevation_points_c8f6a83c02e171fc81f0c9a6014dc5f0</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.6208670024909" miny="-4.92156772644805" maxx="29.697597952819" maxy="-4.86478023751744"/></FeatureType><FeatureType><Name>geonode:kahama_drain_segments</Name><Title>Kahama Drainage Segments</Title><Abstract>This dataset contains information about locations of drain points of interest in Kahama. These points will identify various features found within the drainage system such as blockages, damaged points, exits, outflows, and others. This dataset will be produced under the Tanzania Urban Resilience Program in Kahama and Kigoma The assignment shall build on previous knowledge of community mapping and open-source digital spatial data collection acquainted with TURP, and in doing so build digital skills and create job opportunities for the students. This dataset will cover Kahama Mjini, Majengo and parts of the Malunga, Nyahanga, Nyihogo, Nyasubi and Mhongolo in Kahama .</Abstract><Keywords>Drainage, features, kahama_drain_segments</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.57156987" miny="-3.856211262130192" maxx="32.63437722700321" maxy="-3.787178434723452"/></FeatureType><FeatureType><Name>geonode:kigoma_drain_points</Name><Title>Kigoma Drainage Points</Title><Abstract>"This dataset will contains information about locations of drain points of interest in Kahama and Kigoma. These points will identify various features found within drainage system such as blockagees, damaged points, exit, outflow and others. This dataset will be produced under the Tanzania Urban Resilience Program in Kahama and Kigoma The assignment shall build on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students. This dataset will cover Machinjioni, Kasimbu, Rubuga, Kasingirima, Majengo, Kitongoni, Kipampa, Rusimbi, Buzebazeba, Mwanga Kusini, Kigoma, Mwanga Kaskazini, Katubuka and parts of Kagera ward in Kigoma."</Abstract><Keywords>infrastructure, kigoma_drain_points, features, Drainage</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.62086215981896" miny="-4.921567726448054" maxx="29.69759795281905" maxy="-4.864498586574744"/></FeatureType><FeatureType><Name>geonode:kinondoni_flood_experience</Name><Title>Kinondoni Historical Flood Experiences</Title><Abstract>This data set contains information whether or not a household has experienced flooding in the are of Kinondoni district. If the household has experienced flooding, also the information of whether they had to move from their home was recorded. This data set was collected in the Ramani Huria mapping project hosted by Humanitarian OpenStreetMap Team (HOT) in 2017 and 2018 by surveying local residents. . This data set is part of the Dar es Salaam Historical Flood Experience data set. Part of the data covering Kinondoni district was extracted to enhance the GIS analysis processings since the original whole data is very large.</Abstract><Keywords>flood, hazard, Flood mitigation, flood experience, features, kinondoni_flood_experience</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.23521566" miny="-6.8196196" maxx="39.27246" maxy="-6.7869736"/></FeatureType><FeatureType><Name>geonode:output_19017_hazard_map_mean_24306de437f136381</Name><Title>METEOR Project Seismic Hazard Map for Tanzania</Title><Abstract>Seismic Hazard Map showing mean Peak Ground Acceleration (PGA) in g for a 10% probability of exceedence in 50 years for the country of Tanzania. This layer was uploaded as part of the METEOR Project, please see http://meteor-project.org/ for details. If you find this data useful, please please provide feedback via our questionnaire, it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 This map was produced using the GEM OpenQuake engine using the SSAHARA model produced, please see https://hazard.openquake.org/gem/models/SSA/ for further details. Cite this work as: Poggi, V., Durrheim, R., Mavonga Tuluka, G., Weatherill, G., Gee, R., Pagani, M., Nyblade, A., Delvaux, D., 2017. Assessing Seismic Hazard of the East African Rift: a pilot study from GEM and AfricaArray. Bulletin of Earthquake Engineering. Volume 15, Issue 11, 4499–4529, DOI: 10.1007/s10518-017-0152-4 © 2021 GEM Foundation and the METEOR Project Consortium.</Abstract><Keywords>METEOR, hazard, features, output_19017_hazard_map_mean_24306de437f136381, earthquake</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.34517" miny="-11.72812" maxx="40.43317" maxy="-1.00012"/></FeatureType><FeatureType><Name>geonode:morogoro_drain_points_f02d30ec5bbb013a6242b4e29221fa62</Name><Title>Morogoro Drainage Points</Title><Abstract>This dataset contains information about the elevation of drain points of interest in Morogoro. This dataset was produced under the Tanzania Urban Resilience Program. The assignment shall build on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students.</Abstract><Keywords>urban infrastructure, Drainage, morogoro_drain_points_f02d30ec5bbb013a6242b4e29221fa62, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="37.62601208165365" miny="-6.858604671666665" maxx="37.71545253833334" maxy="-6.770783814334636"/></FeatureType><FeatureType><Name>geonode:morogoro_drain_points</Name><Title>Morogoro Drainage Points Elevations</Title><Abstract>This dataset contains information about the elevation of drain points of interest in Morogoro. This dataset was produced under the Tanzania Urban Resilience Program. The assignment shall build on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students.</Abstract><Keywords>urban infrastructure, Drainage, features, morogoro_drain_points</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="37.62601208165365" miny="-6.858604671666665" maxx="37.71545253833334" maxy="-6.770783814334636"/></FeatureType><FeatureType><Name>geonode:morogoro_drain_segments</Name><Title>Morogoro Drainage Segments</Title><Abstract>This dataset contains information about locations of drain segments in Morogoro, This data was obtained from a field surveys in some of the Morogoro municipality wards. The dataset was produced under the Tanzania Urban Resilience Program in Morogoro. The assignment built on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students.</Abstract><Keywords>morogoro_drain_segments, features, Morogoro_drain_segments</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="37.62601208165365" miny="-6.858604671666665" maxx="37.71545253833334" maxy="-6.770783814334636"/></FeatureType><FeatureType><Name>geonode:morogoro_tree_mapping_f749cf095b21d14514abfc90ed3f8f87</Name><Title>Morogoro Tree Mapping</Title><Abstract>Tree mapping was done within Mazimbu campus, Morogoro, where Students collected information and locations of total of 1269 trees. Tree mapping involves collecting data from all trees natural and planted that have diameter of 5cm or above. The dataset contains also information of tree species, whether it is indigenous or not and the diameter and height. The data was collected during Resilience Academy industrial placement 2020 by Sokoine University of Agriculture students.</Abstract><Keywords>environment, natural, trees, morogoro_tree_mapping_f749cf095b21d14514abfc90ed3f8f87, tree species, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="37.62473167" miny="-6.799143333" maxx="37.633405" maxy="-6.792005"/></FeatureType><FeatureType><Name>geonode:shore_msimbaziriver_surveydata_cd_february2019</Name><Title>Msimbazi Reference Elevation Data</Title><Abstract>Reference elevation data collected with a Leica GNSS receiver base station, RTK-GNSS survey pole, and Single Bean Echo Sounding kit for the bathymetric measurements. Horizontal datum: WGS84 UTM 37S Vertical datum: WGS84 ellipsoid Processing was conducted by CDR International and Shore monitoring.</Abstract><Keywords>elevation, features, EPSG:4326, shore_msimbaziriver_surveydata_cd_february2019, hydrology, survey data</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.25455615802744" miny="-6.818621644608205" maxx="39.28836374173562" maxy="-6.793262237284131"/></FeatureType><FeatureType><Name>geonode:msimbazi_charrette_boundary_20180706</Name><Title>Msimbazi River Valley Planning Area Boundary_ 2018</Title><Abstract>Boundary for the Msimbazi River Valley Planning Area, which is a pipeline project that aims to enable spatial planning within the Msimbazi River Valley and to cater for flood safety. This dataset has been initialised by the Ministry of Lands, and verified by the CDR International by fieldwork and stakeholder consultations for the purposes of Msimbazi Charrette project. Msimbazi Charette project identified the investments to be done in the Msimbazi River Valley Project in 2018.</Abstract><Keywords>features, Msimbazi Charrette, msimbazi_charrette_boundary_20180706</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.115464014293295" miny="-6.884581323379906" maxx="39.28612953296545" maxy="-6.78615554860956"/></FeatureType><FeatureType><Name>geonode:mtwara_final_buildings</Name><Title>Mtwara Buildings</Title><Abstract>This building data was collected in Mtwara as part of the data collection process to support the digitization of buildings, roads, and waste accumulation sites. The data was collected through drone imagery to obtain information on the location, size, and condition of buildings in Mtwara.</Abstract><Keywords>mtwara_final_buildings, features, Mtwara, buildings, Tanzania</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="40.1461388" miny="-10.3091371" maxx="40.2083046" maxy="-10.2537399"/></FeatureType><FeatureType><Name>geonode:eo4sd_mtwara_transport_2017</Name><Title>Mtwara Roads Tanzania</Title><Abstract>This data was collected as part of the comprehensive approach to understanding the baseline situation of litter management systems in Mtwara. The highway road data provided valuable information on the presence of litter and sand on the roads, the condition of the roads, and the responsible entities for road cleaning and maintenance. This data is essential for assessing the distribution of litter in the city and understanding the environmental and social impacts of litter. Additionally, highway data was collected to identify potential leakage points of waste into the environment, contributing to a more holistic understanding of the litter management challenges in Mtwara.</Abstract><Keywords>Mtwara, eo4sd_mtwara_transport_2017, features, road, highway</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="40.12167005359405" miny="-10.322314514871378" maxx="40.21001328108283" maxy="-10.25425211085628"/></FeatureType><FeatureType><Name>geonode:mtwara_waste_collection_points</Name><Title>Mtwara Solid Waste Collection Point</Title><Abstract>This data was collected as part of the data collection process to obtain information on the availability, frequency, and reliability of solid waste collection and environmental cleaning services in Mtwara.</Abstract><Keywords>features, solid waste, Mtwara, mtwara_waste_collection_points, Tanzania</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="40.1557373475352" miny="-10.3071952955985" maxx="40.1954184139549" maxy="-10.261741948705"/></FeatureType><FeatureType><Name>geonode:buildings</Name><Title>Mwanza Buildings</Title><Abstract>This dataset contains information about buildings in Mwanza city. This data was created from remote digitization of building footprints using satelite imagery and participatory mapping in Nyamagana and Ilemela municipalities. This dataset was produced under the project Community Mapping Urban risks in Mwanza to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>features, urban environment, buildings, exposure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8620827" miny="-2.6524112" maxx="33.08088712628851" maxy="-2.3684468"/></FeatureType><FeatureType><Name>geonode:mwanza_businesses</Name><Title>Mwanza Businesses</Title><Abstract>This dataset contains information about businesses in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>exposure, features, mwanza_businesses, shops, businesses</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8787971" miny="-2.6340095" maxx="32.9739866" maxy="-2.4463882"/></FeatureType><FeatureType><Name>geonode:mwanza_businesses_1ee0de54004d225e705484644af28018</Name><Title>Mwanza City Businesses</Title><Abstract>This dataset contains information about businesses in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>features, mwanza_businesses_1ee0de54004d225e705484644af28018, shops, businesses, exposure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8787971" miny="-2.6340095" maxx="32.9739866" maxy="-2.4463882"/></FeatureType><FeatureType><Name>geonode:mwanza_drainage_points</Name><Title>Mwanza Drainage Points</Title><Abstract>This dataset contains information about locations of drain points of interest in Mwanza city. These points identify various features found within drainage system such as blockagees, damaged points, exit, outflow and others. This data was obtained from field survey in Ilemela and Nyamagana. This dataset was produced under the Community Mapping Urban risks project in Mwanza which aims to generate up-to-date open data on drainage for flood modeling purposes. This dataset covers the Ibungilo, Ilemela, Mecco, Buzuruga, Nyamanoro, Kirumba, Kitangili, Pasiansi, Kirumba and Kawekamo for Ilemela municipality and for Nyamagana Municipality were Butimba, Mkuyuni, Mabatini, Pamba, Isamilo, Mirongo, Mbugani and Igogo. These wards were 18 in total for both municipalities. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>mwanza_drainage_points, exposure, Drainage, features, urban infrastructure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.88218822264999" miny="-2.5754822" maxx="32.96732693110052" maxy="-2.443082078303363"/></FeatureType><FeatureType><Name>geonode:existing_ferry_route</Name><Title>Mwanza Existing Ferry Route</Title><Abstract>Existing Ferry Route dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>existing_ferry_route, features, Existing, Route, Ferry</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="31.75063333707233" miny="-2.5429472671900477" maxx="34.73883582131151" maxy="0.2939965805793807"/></FeatureType><FeatureType><Name>geonode:existing_landfill_site</Name><Title>Mwanza Existing Landfill Site</Title><Abstract>Existing Landfill Site dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Landfill, features, Site, Existing, existing_landfill_site</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.903174145944156" miny="-2.6393357769957544" maxx="32.96759095537783" maxy="-2.466904069972752"/></FeatureType><FeatureType><Name>geonode:existing_road_centreline</Name><Title>Mwanza Existing Road Centreline</Title><Abstract>Existing Road Centreline dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, road, existing_road_centreline, Centreline</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86482330150831" miny="-2.730594177749905" maxx="33.105506030402495" maxy="-2.373163269507682"/></FeatureType><FeatureType><Name>geonode:existing_sewer_network</Name><Title>Mwanza Existing Sewer Network</Title><Abstract>Existing Sewer Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, Service, Network, existing_sewer_network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89133752723142" miny="-2.5290265654710913" maxx="32.916678922168515" maxy="-2.4678436795681926"/></FeatureType><FeatureType><Name>geonode:existing_water_supply_network</Name><Title>Mwanza Existing Water Supply Network</Title><Abstract>Existing Water Supply Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Supply, Existing, water, existing_water_supply_network, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86615139456648" miny="-2.6475943803899296" maxx="33.05679179115283" maxy="-2.442989003767491"/></FeatureType><FeatureType><Name>geonode:mwanza_financial_amenities</Name><Title>Mwanza Financial Amenities</Title><Abstract>This dataset contains information about financial amenities such as banks and ATMs in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>exposure, mwanza_financial_amenities, amenities, features, finance</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8891182" miny="-2.6218129" maxx="32.9534071" maxy="-2.4540071"/></FeatureType><FeatureType><Name>geonode:mwanza_health_facilities</Name><Title>Mwanza Health Facilities</Title><Abstract>This dataset contains information about health facilities such as hospitals and pharmacies in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>amenities, features, exposure, health, clinic, mwanza_health_facilities</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8796422" miny="-2.6339578" maxx="32.9555074" maxy="-2.4503072"/></FeatureType><FeatureType><Name>geonode:mwanza_households_affected_by_rockfall</Name><Title>Mwanza Households Affected by Rockfall</Title><Abstract>This dataset contains information of households affected by rockfall incidents in Mwanza City for the past 10 years. This data was collected by carrying out on-the-ground data collection in areas where rock fall incidents have been reported. Collection was executed by surveying local household residents who have experienced rockfalls. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>disaster, urban environment, features, hazard, mwanza_households_affected_by_rockfall, rockfall</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.88399836" miny="-2.58806" maxx="32.92547333" maxy="-2.47462"/></FeatureType><FeatureType><Name>geonode:mwanza_households_at_risk_of_rockfall</Name><Title>Mwanza Households at Risk of Rockfall</Title><Abstract>This dataset shows areas that are at risk when rockfalls happen within Mwanza City. This data was derived from digitization around areas where rockfalls were likely to happen. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data creation was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>disaster, mwanza_households_at_risk_of_rockfall, urban environment, features, hazard, rockfall</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.88079669455472" miny="-2.634122440927163" maxx="32.9763620875604" maxy="-2.473718068389893"/></FeatureType><FeatureType><Name>geonode:mwanza_offices</Name><Title>Mwanza Offices</Title><Abstract>This dataset contains information about government, private and NGO offices in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>features, mwanza_offices, office, exposure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8801703" miny="-2.6267154" maxx="33.0180519" maxy="-2.4532151"/></FeatureType><FeatureType><Name>geonode:mwanza_other_points_of_interest</Name><Title>Mwanza Other Points of Interest</Title><Abstract>This dataset contains information about general Points of Interest such as bars, libraries and gas stations in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>mwanza_other_points_of_interest, exposure, gas station, amenities, features, library, POI, bar, urban infrastructure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8761231" miny="-2.6285435" maxx="32.9949409" maxy="-2.3992216"/></FeatureType><FeatureType><Name>geonode:place_name</Name><Title>Mwanza Place Name</Title><Abstract>Place Name dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>name, Place, place_name, features</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.880554445140135" miny="-2.717321990637775" maxx="33.200935320428066" maxy="-2.3839728866539285"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_catchment</Name><Title>Mwanza Proposed Drainage Catchment</Title><Abstract>Proposed Drainage Catchment dataset contains spatial data used for the Mwanza Master Plan. The cccdata was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Drainage, features, proposed_drainage_catchment, Proposed, catchments</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86050955411963" miny="-2.7028594752063464" maxx="33.081986121481314" maxy="-2.363435842085926"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_natural_wetlandf040fff6db3d</Name><Title>Mwanza Proposed Drainage Natural Wetland</Title><Abstract>Proposed Drainage Natural Wetland dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>natural, Proposed, features, proposed_drainage_natural_wetlandf040fff6db3d, Natural, Drainage, Wetland</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.88482625156908" miny="-2.6583616855013705" maxx="33.01659496312965" maxy="-2.387899079916215"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_network</Name><Title>Mwanza Proposed Drainage Network</Title><Abstract>Proposed Drainage Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Drainage, features, proposed_drainage_network, Proposed, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8743155954656" miny="-2.6550393540378585" maxx="33.08108354926608" maxy="-2.387934840660068"/></FeatureType><FeatureType><Name>geonode:proposed_electricity_network</Name><Title>Mwanza Proposed Electricity Network</Title><Abstract>Proposed Electricity Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Electricity, Network, proposed_electricity_network, Proposed</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.90120199476456" miny="-2.6795693898590307" maxx="33.035842468261926" maxy="-2.4218245530620868"/></FeatureType><FeatureType><Name>geonode:proposed_ict_shape</Name><Title>Mwanza Proposed ICT Shape</Title><Abstract>Proposed ICT Shape dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Proposed, Shape, ICT, features, proposed_ict_shape</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.87438090699422" miny="-2.669879547254124" maxx="33.04611272029279" maxy="-2.385115604810179"/></FeatureType><FeatureType><Name>geonode:proposed_sewerage_transfer_station</Name><Title>Mwanza Proposed Sewerage Transfer Station</Title><Abstract>Proposed Sewerage Transfer Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement</Abstract><Keywords>Sewerage, features, Proposed, Station, Transfer, proposed_sewerage_transfer_station</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.951957955718065" miny="-2.639475861897017" maxx="32.99284937484352" maxy="-2.4213066900291347"/></FeatureType><FeatureType><Name>geonode:proposed_soild_waste_landfill</Name><Title>Mwanza Proposed Soild Waste Landfill</Title><Abstract>Proposed Soild Waste Landfill dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Landfill, features, solid, Proposed, Waste, proposed_soild_waste_landfill</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="33.00020627037779" miny="-2.616685735523873" maxx="33.04460675139108" maxy="-2.432456540612442"/></FeatureType><FeatureType><Name>geonode:proposed_water_supply_network</Name><Title>Mwanza Proposed Water Supply Network</Title><Abstract>Proposed Water Supply Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, proposed_water_supply_network, water, Supply, Network, Proposed</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.87274664563247" miny="-2.6382542473007766" maxx="33.05579624868077" maxy="-2.382586113186085"/></FeatureType><FeatureType><Name>geonode:mwanza_religious_facilities</Name><Title>Mwanza Religious Facilities</Title><Abstract>This dataset contains information about religious institutions in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>religion, exposure, mosque, features, christian, mwanza_religious_facilities, muslim, church</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.882638" miny="-2.6220272" maxx="33.0188522" maxy="-2.446665"/></FeatureType><FeatureType><Name>geonode:mwanza_roads</Name><Title>Mwanza Roads</Title><Abstract>This dataset contains information about roads in Mwanza city. This data resulted from a data cleaning exercise of existing road data in OpenStreetMap. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data processing was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>mwanza_roads, exposure, infrastructure, features, roads</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8636547" miny="-2.655194983069022" maxx="33.08086004297584" maxy="-2.375680139182044"/></FeatureType><FeatureType><Name>geonode:mwanza_rockfall_locations</Name><Title>Mwanza Rockfall Locations</Title><Abstract>This dataset contains information on locations of rockfalls in Mwanza City for the past 10 years. This data was collected by carrying out on-the-ground data collection in areas where rock fall incidents have been reported. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City. Data collection was executed by Spatial Collective, OpenMap Development Tanzania (OMDTZ), Humanitarian OpenStreetMap Team (HOT), and students from IRDP and SAUT universities in Mwanza.</Abstract><Keywords>urban environment, disaster, mwanza_rockfall_locations, rockfall, features, hazard</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.88093333" miny="-2.633896982" maxx="32.97423363" maxy="-2.4739638"/></FeatureType><FeatureType><Name>geonode:approved_projects</Name><Title>Mwanza approved projects</Title><Abstract>Approved Projects dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>approved_projects, Projects, features, Approved</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86366662820532" miny="-2.6450282236703178" maxx="33.07686014120542" maxy="-2.37286197787487"/></FeatureType><FeatureType><Name>geonode:contour_10m</Name><Title>Mwanza contour_10m</Title><Abstract>Contour 10m dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>contour_10m, 10m, features, Contour</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.7509627149321" miny="-2.920023513289423" maxx="33.28288806760793" maxy="-2.3626130740553912"/></FeatureType><FeatureType><Name>geonode:district_boundaries_9a3af830e8c06df98d4319c7d480c542</Name><Title>Mwanza district boundaries</Title><Abstract>District Boundaries dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>district_boundaries_9a3af830e8c06df98d4319c7d480c542, boundaries, features, districts</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86050831451561" miny="-2.7137055111911845" maxx="33.08198685006592" maxy="-2.363435770613485"/></FeatureType><FeatureType><Name>geonode:mwanza_drainage_points_elevation</Name><Title>Mwanza drainage points elevations</Title><Abstract>This dataset contains information about drainage elevation in Mwanza city. The points of elevation have been captured by using Real Time Kinematik (RTK) as it enables accurately points to be captured with location of up to 2cm error. This data was obtained from field survey in Ilemela and Nyamagana. This dataset was produced under the Community Mapping Urban risks project in Mwanza which aims to generate up-to-date open data on drainage for flood modeling purposes. This dataset covers the Ibungilo, Ilemela, Mecco, Buzuruga, Nyamanoro, Kirumba, Kitangili, Pasiansi, Kirumba and Kawekamo for Ilemela municipality and for Nyamagana Municipality were Butimba, Mkuyuni, Mabatini, Pamba, Isamilo, Mirongo, Mbugani and Igogo. These wards were 18 in total for both municipalities.</Abstract><Keywords>mwanza_drainage_points_elevation, exposure, elevation, Drainage, features, urban infrastructure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8824926" miny="-2.575306225" maxx="32.96770325" maxy="-2.443109675"/></FeatureType><FeatureType><Name>geonode:existing_sewerage_pump_station</Name><Title>Mwanza existing Dumping Site</Title><Abstract>Existing Dumping Site dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Site, Existing, existing_sewerage_pump_station, Dumping</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89883600721918" miny="-2.5453416364848516" maxx="32.90513737235382" maxy="-2.5066864351774645"/></FeatureType><FeatureType><Name>geonode:existing_ict_base_station</Name><Title>Mwanza existing Ict Base Station</Title><Abstract>Existing ICT Base Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>ICT, features, Base, existing_ict_base_station, Existing, Station</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.88482362812429" miny="-2.680454679803448" maxx="33.00479258704312" maxy="-2.4482581067889115"/></FeatureType><FeatureType><Name>geonode:existing_ict_network</Name><Title>Mwanza existing Ict Network</Title><Abstract>Existing ICT Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>ICT, features, Network, Existing, existing_ict_network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.891733986489164" miny="-2.601314716205982" maxx="32.939582971111854" maxy="-2.4434142690129774"/></FeatureType><FeatureType><Name>geonode:existing_service_reservoir</Name><Title>Mwanza existing Service Reservoir</Title><Abstract>Existing Sewer Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement. through stakeholder engagement.</Abstract><Keywords>Reservoir, features, Existing, existing_service_reservoir, Service</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.889719491131665" miny="-2.5971756181019305" maxx="33.03869073242205" maxy="-2.4808306360086534"/></FeatureType><FeatureType><Name>geonode:existing_solid_waste_collection</Name><Title>Mwanza existing Solid Waste Collection</Title><Abstract>Existing Solid Waste Collection dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, existing_solid_waste_collection, Urban, Development, infrastructure, Planning</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89453345129439" miny="-2.6021116438766976" maxx="32.983402440478976" maxy="-2.4579826753855847"/></FeatureType><FeatureType><Name>geonode:existing_water_supply_intake</Name><Title>Mwanza existing Water Supply Intake</Title><Abstract>Existing Water Supply Intake dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Supply, Existing, water, Intake, existing_water_supply_intake</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.88577891209987" miny="-2.58525570888261" maxx="32.899911266353726" maxy="-2.5262058135269774"/></FeatureType><FeatureType><Name>geonode:existing_electricity_network</Name><Title>Mwanza existing electricity network</Title><Abstract>Existing Electricity Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, Network, Electricity, existing_electricity_network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.9557860796369" miny="-2.637261862227654" maxx="33.041418061673276" maxy="-2.5414335094959166"/></FeatureType><FeatureType><Name>geonode:existing_electricity_sub_stations</Name><Title>Mwanza existing electricity sub stations</Title><Abstract>Existing Electricity Sub Stations dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>existing_electricity_sub_stations, Stations, features, Existing, Sub, Electricity</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.90320207180871" miny="-2.5708082279460793" maxx="32.96622985841032" maxy="-2.4701932512892895"/></FeatureType><FeatureType><Name>geonode:existing_landuse_plan</Name><Title>Mwanza existing landuse plan</Title><Abstract>Existing Landuse Plan dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, landuse, Plan, Existing, existing_landuse_plan</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.860506105401775" miny="-2.732927072447428" maxx="33.106590831564716" maxy="-2.363435770613485"/></FeatureType><FeatureType><Name>geonode:existing_dumping_site_99d0d83636763fbbcfdcd1bcc3f7ea96</Name><Title>Mwanza existing main dumping site</Title><Abstract>Existing Dumping Site dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Site, existing_dumping_site_99d0d83636763fbbcfdcd1bcc3f7ea96, Existing, Dumping</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.945194949729725" miny="-2.639888081974877" maxx="33.038311074143714" maxy="-2.3947454015735223"/></FeatureType><FeatureType><Name>geonode:existing_natural_drainage_network</Name><Title>Mwanza existing natural drainage network</Title><Abstract>Existing Natural Drainage Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Drainage, features, Natural, Existing, existing_natural_drainage_network, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.87441669386142" miny="-2.7156174788404015" maxx="33.09482344967396" maxy="-2.378453813969353"/></FeatureType><FeatureType><Name>geonode:existing_town_planning_schemes</Name><Title>Mwanza existing town planning schemes</Title><Abstract>Existing Town Planning Schemes dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, Town, existing_town_planning_schemes, Schemes, Planning</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.861299522944634" miny="-2.652924785882868" maxx="33.04545010919102" maxy="-2.3745444651874217"/></FeatureType><FeatureType><Name>geonode:existing_ward_wise_land_values</Name><Title>Mwanza existing wardwise land values</Title><Abstract>Existing Ward Wise Land Values dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, Ward, Wise, Values, land, existing_ward_wise_land_values</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86084184235208" miny="-2.6552569336693663" maxx="33.157221437897206" maxy="-2.257940985933883"/></FeatureType><FeatureType><Name>geonode:existing_wardwise_population_densities</Name><Title>Mwanza existing wardwise population densities</Title><Abstract>Existing Wardwise Population Densities dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, Wardwise, Population, Densities, existing_wardwise_population_densities</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86084184235208" miny="-2.6552569336693663" maxx="33.157221437897206" maxy="-2.257940985933883"/></FeatureType><FeatureType><Name>geonode:existing_waste_water_treatment_plant</Name><Title>Mwanza existing waste water treatment plant</Title><Abstract>Existing Waste Water Treatment Plant dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Existing, water, Plant, Treatment, Waste, existing_waste_water_treatment_plant</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.91141105234014" miny="-2.4690692550657434" maxx="32.911429043623656" maxy="-2.4690511595698497"/></FeatureType><FeatureType><Name>geonode:existing_waste_water_treatment_plant7d846b3e0d8e</Name><Title>Mwanza existing waste water treatment plant</Title><Abstract/><Keywords>features, existing_waste_water_treatment_plant7d846b3e0d8e</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.91141105234014" miny="-2.4690692550657434" maxx="32.911429043623656" maxy="-2.4690511595698497"/></FeatureType><FeatureType><Name>geonode:existing_water_supply_zone</Name><Title>Mwanza existing water supply zone</Title><Abstract>Existing Water Supply Zone dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>existing_water_supply_zone, features, Supply, Existing, water</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8612276723559" miny="-2.713705509998235" maxx="33.08188848118193" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:landmark</Name><Title>Mwanza landmark</Title><Abstract>Landmark dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>landmark, conservation, features</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86510699200136" miny="-2.7160148546541296" maxx="32.9907250914412" maxy="-2.3997698291858094"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_channel_391e6b761af320bb4c37be924ed17b83</Name><Title>Mwanza proposed Drainage Channel</Title><Abstract>Proposed Drainage Channel dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement</Abstract><Keywords>Drainage, features, Channel, Proposed, proposed_drainage_channel_391e6b761af320bb4c37be924ed17b83</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89460203456525" miny="-2.655839431381393" maxx="33.08161203152701" maxy="-2.383665412410907"/></FeatureType><FeatureType><Name>geonode:proposed_ict_network</Name><Title>Mwanza proposed Ict network</Title><Abstract>Proposed ICT Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>proposed_ict_network, Proposed, ICT, features, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.872937023708985" miny="-2.7051342431190157" maxx="33.06034965125732" maxy="-2.3846127927136793"/></FeatureType><FeatureType><Name>geonode:proposed_planning_zone_boundaries569743b61cdd</Name><Title>Mwanza proposed Planning Zone Boundaries</Title><Abstract>Proposed Planning Zone Boundaries dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Zone, boundaries, features, Proposed, proposed_planning_zone_boundaries569743b61cdd, Planning</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8612276723559" miny="-2.713705509998235" maxx="33.08188848118193" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:proposed_solid_waste_collection_zone</Name><Title>Mwanza proposed Solid Waste Collection Zone</Title><Abstract>Proposed Solid Waste Collection Zone dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Zone, proposed_solid_waste_collection_zone, solid, features, Proposed, Waste, Collection</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86123427446807" miny="-2.6551215175396345" maxx="33.08188458531649" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:proposed_stp_pumping_station_transfer_station</Name><Title>Mwanza proposed Stp Pumping Station Transfer Station</Title><Abstract>Proposed STP Pumping Station Transfer Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>STP, features, Proposed, Station, Pumping, Transfer, proposed_stp_pumping_station_transfer_station</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86608933733921" miny="-2.6541793889606526" maxx="33.009148026886024" maxy="-2.3742910638140047"/></FeatureType><FeatureType><Name>geonode:proposed_urban_design_planning_boundary</Name><Title>Mwanza proposed Urban Design Planning Boundary</Title><Abstract>Proposed Urban Design Planning Boundary dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, proposed_urban_design_planning_boundary, Proposed, boundary, Urban, Planning, Design</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8905762184764" miny="-2.5269717073225784" maxx="32.90849026615983" maxy="-2.505279905702135"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_channel</Name><Title>Mwanza proposed Water Distribution Centre - Line</Title><Abstract>Proposed Water Distribution Centre dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement</Abstract><Keywords>features, Centre, water, Distribution, proposed_drainage_channel, Proposed</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89460203456525" miny="-2.655839431381393" maxx="33.08161203152701" maxy="-2.383665412410907"/></FeatureType><FeatureType><Name>geonode:proposed_water_distribution_centre</Name><Title>Mwanza proposed Water Distribution Centre - Points</Title><Abstract>Proposed Water Distribution Centre dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Centre, water, Distribution, proposed_water_distribution_centre, Proposed</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.872382233709885" miny="-2.633788558707121" maxx="33.05249665546979" maxy="-2.4187204428878646"/></FeatureType><FeatureType><Name>geonode:proposed_water_supply_intake</Name><Title>Mwanza proposed Water Supply Intake</Title><Abstract>Proposed Water Supply Intake dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Supply, Intake, water, Proposed, proposed_water_supply_intake</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.980032799414545" miny="-2.3805621047710694" maxx="32.98005078861393" maxy="-2.3805440101719477"/></FeatureType><FeatureType><Name>geonode:proposed_water_supply_zone</Name><Title>Mwanza proposed Water Supply Zone</Title><Abstract>Proposed Water Supply Zone dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Zone, features, Supply, Proposed, water, proposed_water_supply_zone</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8612276723559" miny="-2.713705509998235" maxx="33.08188848118193" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:proposed_bus_rapid_transit_network</Name><Title>Mwanza proposed bus rapid transit network</Title><Abstract>Proposed Bus Rapid Transit Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Bus, features, Proposed, Transit, Rapid, proposed_bus_rapid_transit_network, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89467008410617" miny="-2.6246104584889043" maxx="32.99534787127501" maxy="-2.4413662533729688"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_detention_pond</Name><Title>Mwanza proposed drainage detention pond</Title><Abstract>Proposed Drainage Detention Pond dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Drainage, proposed_drainage_detention_pond, features, Proposed, ponds, detetion</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.89790631642361" miny="-2.498419100235235" maxx="32.9049103931403" maxy="-2.4871092134797563"/></FeatureType><FeatureType><Name>geonode:proposed_drainage_natural_wetland</Name><Title>Mwanza proposed drainage natural wetland</Title><Abstract/><Keywords>features, proposed_drainage_natural_wetland</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.88482625156908" miny="-2.6583616855013705" maxx="33.01659496312965" maxy="-2.387899079916215"/></FeatureType><FeatureType><Name>geonode:proposed_electric_sub_station</Name><Title>Mwanza proposed electric sub station</Title><Abstract>Proposed Electric Sub Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>proposed_electric_sub_station, features, Proposed, Station, Electric, Sub</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.90305870314411" miny="-2.635993771563483" maxx="33.024839524116516" maxy="-2.439635201383949"/></FeatureType><FeatureType><Name>geonode:proposed_environment_treatment_zone</Name><Title>Mwanza proposed environment treatment zone</Title><Abstract>Proposed Environment Treatment Zone dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Zone, proposed_environment_treatment_zone, environment, features, Proposed, Treatment</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.94620444905341" miny="-2.6461194428173163" maxx="32.95780891036206" maxy="-2.49019712318336"/></FeatureType><FeatureType><Name>geonode:proposed_road_right_of_way</Name><Title>Mwanza proposed road right of way</Title><Abstract>Proposed Road Right of Way dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, Proposed, road, Way, proposed_road_right_of_way, Right</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.863075666730175" miny="-2.731803411716374" maxx="33.092512124801196" maxy="-2.373347547422056"/></FeatureType><FeatureType><Name>geonode:proposed_sewer_network</Name><Title>Mwanza proposed sewer network</Title><Abstract>Proposed Sewer Network dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>proposed_sewer_network, features, Proposed, Sewer, Network</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.866089314333564" miny="-2.654393372370855" maxx="33.02247413353412" maxy="-2.37381615472539"/></FeatureType><FeatureType><Name>geonode:proposed_sewerage_constructed_wetland</Name><Title>Mwanza proposed sewerage constructed wetland</Title><Abstract>Proposed Sewerage Constructed Wetland dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Sewerage, proposed_sewerage_constructed_wetland, features, Proposed, Wetland, Constructed</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.92503000095809" miny="-2.645665655266574" maxx="33.02615582714554" maxy="-2.480010049622866"/></FeatureType><FeatureType><Name>geonode:proposed_solid_waste_transfer_station</Name><Title>Mwanza proposed solid waste transfer station</Title><Abstract>Proposed Solid Waste Transfer Station dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>features, solid, Proposed, Station, proposed_solid_waste_transfer_station, Transfer, Waste</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.951957955718065" miny="-2.639475861897017" maxx="32.99284937484352" maxy="-2.4213066900291347"/></FeatureType><FeatureType><Name>geonode:regional_boundaries</Name><Title>Mwanza regional boundaries</Title><Abstract>Regional Boundaries dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>regional_boundaries, Regional, boundaries, features</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="31.93248364460408" miny="-3.437801345910545" maxx="33.79105337096991" maxy="-1.669479609380604"/></FeatureType><FeatureType><Name>geonode:ward_boundaries_3f7b0f55ee9ba5ff1b1d6823c209cd35</Name><Title>Mwanza ward boundaries</Title><Abstract>Ward Boundaries dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>boundaries, ward_boundaries_3f7b0f55ee9ba5ff1b1d6823c209cd35, features, Ward</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86117714918455" miny="-2.655109160194678" maxx="33.08188458450372" maxy="-2.3728551756585428"/></FeatureType><FeatureType><Name>geonode:nungwi_art_centers</Name><Title>Nungwi Art Centers</Title><Abstract>This dataset contains information about art spaces in Nungwi. Art centers are shops in which artist showcase some of their art works as well as act as an art studio in which they create their art pieces. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>art, art centers, nungwi_art_centers, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.290923708252244" miny="-5.736431885099842" maxx="39.29866655718065" maxy="-5.725709916598728"/></FeatureType><FeatureType><Name>geonode:nungwi_buildings</Name><Title>Nungwi Buildings</Title><Abstract>This dataset contains information about the built nature and use of buildings in Nungwi area. The geometry was sourced from the Commission for Lands and from OpenStreetMap while the other attributes were attached to the geometry during a fieldwork expedition in Nungwi. This dataset was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>infrastructure, buildings, features, nungwi_buildings</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.28919876472999" miny="-5.743631106310066" maxx="39.31302874892266" maxy="-5.72221279493769"/></FeatureType><FeatureType><Name>geonode:nungwi_businesses</Name><Title>Nungwi Businesses</Title><Abstract>This dataset contains information about businesses in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>businesses, features, shops, nungwi_businesses</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.290430622992794" miny="-5.742573892337434" maxx="39.30997697542842" maxy="-5.722545916011199"/></FeatureType><FeatureType><Name>geonode:nungwi_community_centers_0ef07a3eeb1f5579c71a6d94efe298d3</Name><Title>Nungwi Community Centers</Title><Abstract>This dataset contains information about locations of public community spaces in Nungwi. A community center is a social space where community members congregate for various purposes such as leisure, meetings etc. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>social, communication, features, nungwi_community_centers_0ef07a3eeb1f5579c71a6d94efe298d3, community</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29432212480359" miny="-5.737855912112262" maxx="39.303275992566526" maxy="-5.723916883781329"/></FeatureType><FeatureType><Name>geonode:ningwi_community_heritage</Name><Title>Nungwi Community Heritage</Title><Abstract>This dataset contains information about locations of areas of cultural significance to the local community in Nungwi. Community heritage in this case means important sites/places/things which have significance to the local community of Nungwi. This data was obtained from a community walk together with local guides from within the community in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, tourism, culture, recreation, ningwi_community_heritage</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.295001" miny="-5.729321" maxx="39.300357" maxy="-5.722976"/></FeatureType><FeatureType><Name>geonode:nungwi_craft_workshops</Name><Title>Nungwi Craft Workshops</Title><Abstract>This dataset contains information about crafts in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>crafts, features, painting, nungwi_craft_workshops, arts</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29208442143086" miny="-5.739123875928084" maxx="39.301865996896574" maxy="-5.722900948533137"/></FeatureType><FeatureType><Name>geonode:nungwi_dining_and_recreation</Name><Title>Nungwi Dining and Recreation</Title><Abstract>This dataset contains information about locations of eateries and recreational areas in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>amenities, dining, features, tourism, nungwi_dining_and_recreation, recreation</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.28823361330242" miny="-5.750087006370434" maxx="39.309598425367696" maxy="-5.722718158654486"/></FeatureType><FeatureType><Name>geonode:nungwi_education_facilities</Name><Title>Nungwi Education Facilities</Title><Abstract>This dataset contains information about learning institutions in Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>nungwi_education_facilities, education, amenities, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29344240464585" miny="-5.741666945566855" maxx="39.3028329434684" maxy="-5.723248919519572"/></FeatureType><FeatureType><Name>geonode:nungwi_health_facilities</Name><Title>Nungwi Health Facilities</Title><Abstract>This dataset contains information about medical institutions in Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>health, amenities, features, clinic, nungwi_health_facilities</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29304058821926" miny="-5.733819610387461" maxx="39.29845599207806" maxy="-5.727041011899185"/></FeatureType><FeatureType><Name>geonode:nungwi_hotels</Name><Title>Nungwi Hotels</Title><Abstract>This dataset contains information about locations and service information of hotels in Nungwi. This data was collected through a site visit of hotels in the area. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>hotels, tourism, accommodation, features, recreation, nungwi_hotels</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.291616848325475" miny="-5.735903817940202" maxx="39.311463417729044" maxy="-5.723425473485442"/></FeatureType><FeatureType><Name>geonode:nungwi_information_signs</Name><Title>Nungwi Information Signs</Title><Abstract>This dataset contains information about physical signage in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>nungwi_information_signs, infrastructure, communication, features, information</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.28811305939129" miny="-5.750708551275962" maxx="39.306351" maxy="-5.722488"/></FeatureType><FeatureType><Name>geonode:nungwi_inland_waters</Name><Title>Nungwi Inland Waters</Title><Abstract>This dataset contains geometries of inland waters in Nungwi. This data was obtained from digitization of drone imagery and field verification survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, nungwi_inland_waters</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.30278479376918" miny="-5.724133102742839" maxx="39.30370942969111" maxy="-5.722254345834618"/></FeatureType><FeatureType><Name>geonode:nungwi_landuse</Name><Title>Nungwi Land Use</Title><Abstract>This dataset approximates the current land use in Nungwi. This data was derived from a building survey that was done in the entire Nungwi area. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, nungwi_landuse, land use</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.28873231165042" miny="-5.742957927037354" maxx="39.31319583827833" maxy="-5.72191385596687"/></FeatureType><FeatureType><Name>geonode:nungwi_playgrounds</Name><Title>Nungwi Playgrounds</Title><Abstract>This dataset contains information about playgrounds in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, nungwi_playgrounds, playgrounds, open spaces</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.290067523954946" miny="-5.73619135897113" maxx="39.311095377957145" maxy="-5.725433453829729"/></FeatureType><FeatureType><Name>geonode:nungwi_protected_areas</Name><Title>Nungwi Protected Areas</Title><Abstract>This dataset contains the location of the protected biodiversity area in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>biodiversity, lighthouse, conservation, features, nungwi_protected_areas</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.30249984816104" miny="-5.723469876069896" maxx="39.30403336218257" maxy="-5.721921301361488"/></FeatureType><FeatureType><Name>geonode:nungwi_religious_facilities</Name><Title>Nungwi Religious Facilities</Title><Abstract>This dataset contains information about religious institutions in Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>amenities, nungwi_religious_facilities, religion, features</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29240386234588" miny="-5.741404612709577" maxx="39.30143669202229" maxy="-5.724379354498963"/></FeatureType><FeatureType><Name>geonode:nungwi_roads</Name><Title>Nungwi Roads</Title><Abstract>This dataset contains information about roads in Nungwi area. The geometry was sourced from OpenStreetMap while the other attributes were attached to the geometry during a fieldwork expedition in Nungwi. This dataset was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>exposure, highways, infrastructure, features, nungwi_roads, road</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.284652479422284" miny="-5.840222212560735" maxx="39.32270538435216" maxy="-5.722209475119807"/></FeatureType><FeatureType><Name>geonode:nungwi_solid_waste_management</Name><Title>Nungwi Solid Waste Management</Title><Abstract>This dataset contains information about locations of waste disposal points Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>trash, waste management, amenities, features, sanitation, nungwi_solid_waste_management</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29269392835113" miny="-5.741849908138914" maxx="39.30891974817053" maxy="-5.723421877020718"/></FeatureType><FeatureType><Name>geonode:nungwi_street_lighting</Name><Title>Nungwi Street Lighting</Title><Abstract>This dataset contains information about locations of streetlights (public and private) in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>infrastructure, features, utilities, lighting, nungwi_street_lighting</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.289962960055874" miny="-5.73620190601272" maxx="39.29802318377416" maxy="-5.724906538482586"/></FeatureType><FeatureType><Name>geonode:nungwi_swimming_pools</Name><Title>Nungwi Swimming Pools</Title><Abstract>This dataset contains swimming pools as digitized from drone imagery. Verification of this features was done by a field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>swimming pools, water, features, nungwi_swimming_pools, leisure, hotels</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.289592045675064" miny="-5.741440901350514" maxx="39.31263365304967" maxy="-5.722855452182504"/></FeatureType><FeatureType><Name>geonode:nungwi_toilets</Name><Title>Nungwi Toilets</Title><Abstract>This dataset contains information about locations of toilets in Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>amenities, toilets, features, sanitation, WC, nungwi_toilets</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29374899965233" miny="-5.741565587673103" maxx="39.30471069190679" maxy="-5.72315578166006"/></FeatureType><FeatureType><Name>geonode:nungwi_tourist_attractions</Name><Title>Nungwi Tourist Attractions</Title><Abstract>This dataset contains information about tourist attactions in Nungwi. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, zoo, nungwi_tourist_attractions, conservation, tourist attractions</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.30270592168722" miny="-5.724638222781489" maxx="39.30483541185911" maxy="-5.722313224297604"/></FeatureType><FeatureType><Name>geonode:nungwi_trees</Name><Title>Nungwi Trees</Title><Abstract>This dataset contains information about tree cover in Nungwi. This data was obtained from field survey in Nungwi as well as digitization on high resolution imagery. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>urban ecology, features, nungwi_trees, trees</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.2888393472985" miny="-5.744897517876384" maxx="39.318484470326666" maxy="-5.722131442971923"/></FeatureType><FeatureType><Name>geonode:nungwi_useful_services</Name><Title>Nungwi Useful Services</Title><Abstract>This dataset contains information about points of interest in Nungwi, such as ATMs, gas stations and money exchange services. This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>utilities, nungwi_useful_services, amenities, features, infrastructure, POI</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.291411223956935" miny="-5.742866345940455" maxx="39.30116019057784" maxy="-5.726635212290615"/></FeatureType><FeatureType><Name>geonode:nungwi_water_points</Name><Title>Nungwi Water Points</Title><Abstract>This dataset contains information about locations of water points Nungwi This data was obtained from field survey in Nungwi. It was produced under the project Resilience Academy – Nungwi mapping which aims at generating up-to-date open data for the upcoming town upgrading activities. The mapping was overseed by Spatial Collective, and conducted by students from the State University of Zanzibar (SUZA) undertaking Bsc in Information Technology and Application namagement, Bsc Computer Science and BA in Geography and Environmental Science. This dataset covers the Kiungani and Bandakuu Shehias in the Kaskazini A district in Nungwi.</Abstract><Keywords>features, water, nungwi_water_points, amenities</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29391276252863" miny="-5.742715918265483" maxx="39.30386097547955" maxy="-5.72401493761567"/></FeatureType><FeatureType><Name>geonode:nungwi_water_points_0255c1114173fd8aa80c2dadab1312c2</Name><Title>Nungwi Water Points</Title><Abstract>The Nungwi Water Points dataset provides geospatial information on water access points within Nungwi, located in the northern part of Unguja Island, Zanzibar, United Republic of Tanzania. Compiled by Msilikale Msilanga and published on March 5, 2025, the dataset documents inland water resources with a focus on drinking water and public water supply systems. It includes detailed attributes and asset information relevant to watershed management, community access, and sustainable water use. This dataset supports research, planning, and decision-making related to water resource management, public health, and local infrastructure development in coastal communities of Zanzibar.</Abstract><Keywords>nungwi_water_points_0255c1114173fd8aa80c2dadab1312c2, features, drinking water, watershed, public water</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.29391276252863" miny="-5.742715918265483" maxx="39.30386097547955" maxy="-5.72401493761567"/></FeatureType><FeatureType><Name>geonode:pemba_island_orthophoto_infogrid</Name><Title>Pemba Island Orthophoto_ 7cm 2018</Title><Abstract>High-resolution, 3-band, true color orthophotos covering most of the Zanzibar Pemba island, excluding some highland parts of the island. A single image covers the area of max 3x3km. Images were mapped with drones during years 2018-2016. Spatial resolution varies between 7-8cm, users are advised to check the resolution of a specific image from image properties. These drone images can be used e.g. as basemaps, reference images or for image analysis. Images were captured during Zanzibar Mapping Initiative project, in collaboration between Tanzania Commission for Science and Technology (COSTECH), Zanzibar Commission for Lands (COLA), State University of Zanzibar (SUZA), DA, Spatialinfo, OBSCOM, Sensefly/Parrot Company and The World Bank. The data can be downloaded through Original Data Source</Abstract><Keywords>features, pemba_island_orthophoto_infogrid</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="39.560167005065125" miny="-5.501198844314135" maxx="39.88478399923173" maxy="-4.849804598867014"/></FeatureType><FeatureType><Name>geonode:proposed_planning_district_boundaries</Name><Title>Proposed Planning District Boundaries</Title><Abstract>Proposed Planning District Boundaries dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>boundaries, features, Proposed, districts, proposed_planning_district_boundaries, Planning</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8612276723559" miny="-2.713705509998235" maxx="33.08188848118193" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:proposed_sewerage_zones</Name><Title>Proposed Sewerage Zones</Title><Abstract>Proposed Sewerage Zones dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>Zone, Sewerage, features, Proposed, proposed_sewerage_zones</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8612276723559" miny="-2.713705509998235" maxx="33.08188848118193" maxy="-2.372861735163961"/></FeatureType><FeatureType><Name>geonode:sumbawanga_drain_pointsgpkg_shm</Name><Title>Sumbawanga Drainage Points</Title><Abstract>This dataset contains information about locations of drain segments in Sumbawanga. This data was obtained from field survey in some of the Sumbawanga municipality wards. The dataset produced under the Tanzania Urban Resilience Program. The assignment built on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students.</Abstract><Keywords>urban infrastructure, Drainage, features, sumbawanga_drain_pointsgpkg_shm</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="31.57911806000001" miny="-8.02185935" maxx="31.65410436666667" maxy="-7.925315288333333"/></FeatureType><FeatureType><Name>geonode:sumbawanga_drain_elevations</Name><Title>Sumbawanga Drainage Points Elevations</Title><Abstract>This dataset contains information about the elevation of drain points of interest in Sumbawanga. This dataset was produced under the Tanzania Urban Resilience Program. The assignment shall build on previous knowledge on community mapping and open-source digital spatial data collection acquainted in TURP, and in doing so building digital skills and creating job opportunities for the students.</Abstract><Keywords>sumbawanga_drain_elevations, elevation, features, Drainage, urban infrastructure</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="31.57911806" miny="-8.02185935" maxx="31.6541043666667" maxy="-7.92531528833333"/></FeatureType><FeatureType><Name>geonode:cbd_existing_landuse</Name><Title>Tanga CBD Existing Landuse</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>cbd_existing_landuse, features, Urban, Planning, land use</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.08493280618714" miny="-5.0860611773503805" maxx="39.12690117028315" maxy="-5.054739664326034"/></FeatureType><FeatureType><Name>geonode:commercial_zone</Name><Title>Tanga Commercial zone</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>land use, features, Urban, commercial_zone, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.94070270787685" miny="-5.130404351893448" maxx="38.94461950922144" maxy="-5.127631624211285"/></FeatureType><FeatureType><Name>geonode:conservation_area</Name><Title>Tanga Conservation Area</Title><Abstract>This shapefile represents environmental and conservation areas in Tanga city as outlined in the 2016-2036 masterplan. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>land use, environment, features, conservation_area, conservation</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.897260281644584" miny="-5.273644169828056" maxx="39.139868676878386" maxy="-4.960627880173371"/></FeatureType><FeatureType><Name>geonode:contours_75m</Name><Title>Tanga Contours 75m</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>features, Planning, Urban, contours_75m</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.8543520150544" miny="-5.26861690328993" maxx="39.171240301953446" maxy="-4.95678759799637"/></FeatureType><FeatureType><Name>geonode:epza_area</Name><Title>Tanga EPZA Area</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>epza_area, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.03877911294566" miny="-5.1737448703976545" maxx="39.07421905143366" maxy="-5.127417167612568"/></FeatureType><FeatureType><Name>geonode:existing_landuse</Name><Title>Tanga Existing Landuse</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>existing_landuse, features, Urban, Planning, landuse</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.890293775530054" miny="-5.294944798237569" maxx="39.16397257756358" maxy="-4.961119899748001"/></FeatureType><FeatureType><Name>geonode:facilities</Name><Title>Tanga Facilities</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, facilities, Urban, features</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="38.969292509443704" miny="-5.135921225034028" maxx="39.12597195974532" maxy="-5.058072095602506"/></FeatureType><FeatureType><Name>geonode:improve_revelopmt_upgrading_areas_2</Name><Title>Tanga Improve Development Upgrading Areas</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>improve_revelopmt_upgrading_areas_2, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.90494887629212" miny="-5.253391632995279" maxx="39.135982027684946" maxy="-4.981785847427348"/></FeatureType><FeatureType><Name>geonode:industrial_area</Name><Title>Tanga Industrial Area</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>land use, features, Urban, industrial_area, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.936238120719906" miny="-5.174949104999944" maxx="39.092723346941376" maxy="-4.990481798466788"/></FeatureType><FeatureType><Name>geonode:infilling_residential_developement</Name><Title>Tanga Infilling Residential Development</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>land use, features, Urban, infilling_residential_developement, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.994640156824666" miny="-5.128689750193409" maxx="39.126706328005575" maxy="-5.054728199145717"/></FeatureType><FeatureType><Name>geonode:institutions</Name><Title>Tanga Institutions</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, institutions, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.97714204506602" miny="-5.209946178721854" maxx="39.11872534279732" maxy="-5.013088640346956"/></FeatureType><FeatureType><Name>geonode:kolekole_range_area</Name><Title>Tanga Kolekole range area</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>kolekole_range_area, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.97014219924319" miny="-5.211522276987162" maxx="38.992783123508715" maxy="-5.189212826183552"/></FeatureType><FeatureType><Name>geonode:land_banking</Name><Title>Tanga Land Banking</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, Urban, features, land_banking</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="-179.27015693606447" miny="-89.99859427313189" maxx="-179.27015693606447" maxy="-89.99859427313189"/></FeatureType><FeatureType><Name>geonode:local_roads</Name><Title>Tanga Local Roads</Title><Abstract>This shapefile contains data about roads in Tanga City as part of the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>features, local_roads, roads, infrastructure, Transportation</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.91619495784128" miny="-5.2595200802810265" maxx="39.11729893875519" maxy="-4.980964149596671"/></FeatureType><FeatureType><Name>geonode:main_distribution_pipe</Name><Title>Tanga Main Distribution Pipe</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, water, main_distribution_pipe, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.91619521731252" miny="-5.257579026111343" maxx="39.12593346163591" maxy="-4.973799243293162"/></FeatureType><FeatureType><Name>geonode:main_roads</Name><Title>Tanga Main Roads</Title><Abstract>This shapefile contains data about roads in Tanga City as part of the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, features, Transportation, roads, main_roads</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.89032704599281" miny="-5.294903181113348" maxx="39.12027422206278" maxy="-4.969626950598672"/></FeatureType><FeatureType><Name>geonode:minor_roads</Name><Title>Tanga Minor Roads</Title><Abstract>This shapefile contains data about roads in Tanga City as part of the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>minor_roads, infrastructure, features, Transportation, roads</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.93477233106756" miny="-5.259237404622834" maxx="39.13422305368483" maxy="-4.985255133731865"/></FeatureType><FeatureType><Name>geonode:new_residential_develepment</Name><Title>Tanga New Residential Development</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>land use, features, Urban, new_residential_develepment, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.91392324344273" miny="-5.258925994366911" maxx="39.120705362865515" maxy="-4.980963534317337"/></FeatureType><FeatureType><Name>geonode:pipe_diameter_150_300</Name><Title>Tanga Pipe Diameter 150 300</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, water, pipe_diameter_150_300, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.917962254684205" miny="-5.224678172289908" maxx="39.12525094628104" maxy="-4.997971908725417"/></FeatureType><FeatureType><Name>geonode:tanga_port</Name><Title>Tanga Port</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>tanga_port, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.10095842022406" miny="-5.128621830213495" maxx="39.1189866579594" maxy="-5.063650606396815"/></FeatureType><FeatureType><Name>geonode:proposed_roads</Name><Title>Tanga Proposed Roads</Title><Abstract>This shapefile contains data about roads in Tanga City as part of the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, features, Transportation, roads, proposed_roads</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.75158079727286" miny="-5.230201209974397" maxx="39.07228449954223" maxy="-4.958745523886766"/></FeatureType><FeatureType><Name>geonode:quarry_sites</Name><Title>Tanga Quarry Sites</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, Urban, features, quarry_sites</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.00063284915415" miny="-5.0975263809347835" maxx="39.04258408863813" maxy="-5.060061902515855"/></FeatureType><FeatureType><Name>geonode:cbd_proposed_landuse</Name><Title>Tanga cbd proposed landuse</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>cbd_proposed_landuse, land use, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.08493271314339" miny="-5.0860611773503805" maxx="39.12690117028315" maxy="-5.05402492861466"/></FeatureType><FeatureType><Name>geonode:tanga_city_boundary</Name><Title>Tanga city boundary</Title><Abstract>This shapefile defines administrative or zonal boundaries of Tanga city for the period of 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>administrative, tanga_city_boundary, boundaries, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.89022216440866" miny="-5.295042003726771" maxx="39.164051887091645" maxy="-4.961101803304519"/></FeatureType><FeatureType><Name>geonode:dumping_sites</Name><Title>Tanga dumping sites</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>dumping_sites, features, Urban, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.07468867513488" miny="-5.112426585415532" maxx="39.08958767474465" maxy="-4.986682064639458"/></FeatureType><FeatureType><Name>geonode:hotel_sites</Name><Title>Tanga hotel sites</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Urban, features, hotel_sites, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.07055757528673" miny="-5.257405787391605" maxx="39.12612813686911" maxy="-5.061581017483083"/></FeatureType><FeatureType><Name>geonode:main_supply_pipe</Name><Title>Tanga main supply pipe</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, water, main_supply_pipe, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.96092533360434" miny="-5.096076715035066" maxx="39.07658831688584" maxy="-5.055207889985431"/></FeatureType><FeatureType><Name>geonode:mini_bus_stand_pongwe</Name><Title>Tanga mini bus stand pongwe</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, mini_bus_stand_pongwe, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.97812181751617" miny="-5.1223922892413345" maxx="38.97897845559967" maxy="-5.1213016191246155"/></FeatureType><FeatureType><Name>geonode:new_cbd_boundary</Name><Title>Tanga new cbd boundary</Title><Abstract>This shapefile defines administrative or zonal boundaries of Tanga city for the period of 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>administation, new_cbd_boundary, boundaries, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.08441590292169" miny="-5.086201156421791" maxx="39.12713818354688" maxy="-5.053177967324989"/></FeatureType><FeatureType><Name>geonode:ocean_area</Name><Title>Tanga ocean area</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, ocean_area, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.89801421967739" miny="-5.220900787128129" maxx="39.16395321531942" maxy="-4.969493595121327"/></FeatureType><FeatureType><Name>geonode:ocean_line_boundary</Name><Title>Tanga ocean line boundary</Title><Abstract>         This shapefile defines administrative or zonal boundaries of Tanga city for the period of 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.                                                                                                                                                                                                                   Sheet1                                   This shapefile defines administrative or zonal boundaries of Tanga city for the period of 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>administrative, boundaries, features, ocean_line_boundary</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.04639432452377" miny="-5.257384195431794" maxx="39.136857018350824" maxy="-4.968520480298928"/></FeatureType><FeatureType><Name>geonode:oil_proposed_2</Name><Title>Tanga oil proposed</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, Urban, features, oil_proposed_2</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.084927495673305" miny="-5.072738637724738" maxx="39.126854907252024" maxy="-5.013780548457788"/></FeatureType><FeatureType><Name>geonode:tanga_oil_sites</Name><Title>Tanga oil sites</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Urban, Planning, tanga_oil_sites, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.07939706834035" miny="-5.072739340313304" maxx="39.13280582209286" maxy="-4.9875804270017445"/></FeatureType><FeatureType><Name>geonode:open_pasture</Name><Title>Tanga open pasture</Title><Abstract>This shapefile represents environmental and conservation areas in Tanga city as outlined in the 2016-2036 masterplan. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>open_pasture, environment, features, conservation</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="-179.27015693606447" miny="-89.99859427313189" maxx="-179.27015693606447" maxy="-89.99859427313189"/></FeatureType><FeatureType><Name>geonode:pipeline_buffer_30m</Name><Title>Tanga pipeline buffer 30m</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, water, pipeline_buffer_30m, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.757032105231914" miny="-5.211334759055315" maxx="39.1288722562584" maxy="-5.010410924471791"/></FeatureType><FeatureType><Name>geonode:potentials</Name><Title>Tanga potentials</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>potentials, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.02983925692507" miny="-5.089752072451671" maxx="39.12921141814753" maxy="-5.041221816905463"/></FeatureType><FeatureType><Name>geonode:powerline</Name><Title>Tanga powerline</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Urban, powerline, Planning, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.873928956187484" miny="-5.147047818548188" maxx="39.07086211780306" maxy="-5.082322163416569"/></FeatureType><FeatureType><Name>geonode:powerline_buffer_60m</Name><Title>Tanga powerline buffer 60m</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>powerline_buffer_60m, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.873716705841645" miny="-5.147216291251586" maxx="39.07099500856137" maxy="-5.082085672420776"/></FeatureType><FeatureType><Name>geonode:proposed_small_center</Name><Title>Tanga proposed small center</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, proposed_small_center, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.92362191537243" miny="-5.2558583001973584" maxx="39.11383410117386" maxy="-4.98791839266763"/></FeatureType><FeatureType><Name>geonode:rivers</Name><Title>Tanga rivers</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>features, rivers, Urban, Planning</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="38.915887479087154" miny="-5.106527565732776" maxx="39.127579630918405" maxy="-5.015484574690533"/></FeatureType><FeatureType><Name>geonode:rural_settlement_agriculture</Name><Title>Tanga rural settlement agriculture</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>rural_settlement_agriculture, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.89022059508975" miny="-5.294945061359291" maxx="39.11762875606704" maxy="-4.9626380401839265"/></FeatureType><FeatureType><Name>geonode:service_industries</Name><Title>Tanga service industries</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, Urban, features, service_industries</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.94444785587134" miny="-5.129757937216599" maxx="39.11423093616111" maxy="-5.007691295088284"/></FeatureType><FeatureType><Name>geonode:sisal_estate</Name><Title>Tanga sisal estate</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, sisal_estate, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.96621741290712" miny="-5.249421923432712" maxx="39.03902107005745" maxy="-5.101049124505692"/></FeatureType><FeatureType><Name>geonode:sisal_farms</Name><Title>Tanga sisal farms</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>sisal_farms, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.01369064497751" miny="-5.0718675955244406" maxx="39.07089821274713" maxy="-5.051613100220284"/></FeatureType><FeatureType><Name>geonode:special_residential</Name><Title>Tanga special residential</Title><Abstract>This shapefile provides information on land use planning within Tanga city under the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>special_residential, land use, features, Urban, Planning</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.08741123950544" miny="-5.0793188713715" maxx="39.09354974959193" maxy="-5.068568272853546"/></FeatureType><FeatureType><Name>geonode:storage_tanks</Name><Title>Tanga storage tanks</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>storage_tanks, Planning, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.90880584806131" miny="-5.173058267807176" maxx="39.07185578261031" maxy="-5.055563427928354"/></FeatureType><FeatureType><Name>geonode:tipper_oil_storage</Name><Title>Tanga tipper oil storage</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Urban, tipper_oil_storage, Planning, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.11941243147539" miny="-5.011123662115468" maxx="39.13279331281516" maxy="-5.008027805919125"/></FeatureType><FeatureType><Name>geonode:tourist_attraction_sites</Name><Title>Tanga tourist attraction sites</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, tourist_attraction_sites, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.0247138657871" miny="-5.220376844793207" maxx="39.164032354177714" maxy="-5.048327719834068"/></FeatureType><FeatureType><Name>geonode:wards_boundaries</Name><Title>Tanga wards boundaries</Title><Abstract>This shapefile defines administrative or zonal boundaries of Tanga city for the period of 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>boundaries, administrative, features, wards_boundaries</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.89133370960319" miny="-5.261868449802658" maxx="39.16493567791367" maxy="-4.961119657972797"/></FeatureType><FeatureType><Name>geonode:waterpipe_network</Name><Title>Tanga water pipe network</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>waterpipe_network, water, infrastructure, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.9609293018013" miny="-5.151802107136359" maxx="39.13004650222298" maxy="-5.054665631634319"/></FeatureType><FeatureType><Name>geonode:water_treatment</Name><Title>Tanga water treatment</Title><Abstract>This shapefile shows water infrastructure data within Tanga city from the Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>infrastructure, water, features, water_treatment</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.965888248222555" miny="-5.061125593281355" maxx="38.97138119484421" maxy="-5.055211512579231"/></FeatureType><FeatureType><Name>geonode:zoo</Name><Title>Tanga zoo</Title><Abstract>This shapefile contains spatial data from the Tanga Masterplan 2016-2036. This dataset was developed as part of the comprehensive spatial planning initiative for Tanga City, aligning with sustainable development goals and urban planning standards for the period 2016-2036. It is intended for use by city planners, researchers, policy makers, and other stakeholders involved in urban development and environmental management.</Abstract><Keywords>Planning, zoo, Urban, features</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="38.96035640553694" miny="-5.09960617887946" maxx="38.99198048934253" maxy="-5.082389550665679"/></FeatureType><FeatureType><Name>geonode:tanzania_coralreef_2018</Name><Title>Tanzania Coral Reef</Title><Abstract>The dataset is available for download only through the UN Ocean Data Viewer: https://data.unep-wcmc.org/datasets/1 *** This dataset shows the distribution of coral reefs in Tanzanian coastal regions. This dataset has been clipped from a global coral reef dataset, which is the most comprehensive dataset of warm-water coral reefs to date, acting as a foundation baseline map for future, more detailed, work. This dataset was compiled from a number of sources by UNEP World Conservation Monitoring Centre (UNEP-WCMC) and the World Fish Centre, in collaboration with WRI (World Resources Institute) and TNC (The Nature Conservancy). Data sources include the Millennium Coral Reef Mapping Project (IMaRS-USF and IRD 2005, IMaRS-USF 2005) and the World Atlas of Coral Reefs (Spalding et al. 2001).</Abstract><Keywords>ZanSea, tanzania_coralreef_2018, features, coral reef, environment</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="38.7960069560562" miny="-10.371064700575403" maxx="40.46147214702199" maxy="-4.70216632691438"/></FeatureType><FeatureType><Name>geonode:tanzania_forest_reserves_2020</Name><Title>Tanzania Forest Reserves - 2020</Title><Abstract>This dataset represents all officially mapped and maintained forest reserves in Tanzania. The dataset is from the Tanzania Forest Services (TFS) Agency, and available for download through Protected Planet database: https://www.protectedplanet.net/country/TZA. Latest update was in 2020.</Abstract><Keywords>environment, tanzania_forest_reserves_2020, features, ZanSea, forests, forest, TFS</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.737066269000024" miny="-11.620379343999957" maxx="40.43065642000005" maxy="-1.000471433999962"/></FeatureType><FeatureType><Name>geonode:tanzania_landcover_africover_cb4fe9bf1d2e748e80eaff3b858c6630</Name><Title>Tanzania Landcover, AFRICOVER</Title><Abstract>Original source: http://www.fao.org/geonetwork/srv/en/metadata.show?uuid=29400b68-42a5-4190-af8b-5f3e9d64d022. This dataset is a spatially re-aggregated version of the original national Africover multipurpose database. The original full resolution land cover has been produced from visual interpretation of digitally enhanced LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1997. The data was aggregated by eliminating polygons below a certain area threshold to give priority to the classes belonging to Agriculture. This threshold corresponds to approx. a 30 % reduction in the polygon count. The dataset was then re-aggregated based on area threshold values. For more information on the area thresholds used to spatially aggregate the land cover data, please see the 'spatial-agg-procedure' document available in the original FAO GeoNetwork page linked above.  The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system.  The data set is intended for free public access.</Abstract><Keywords>features, tanzania_landcover_africover_cb4fe9bf1d2e748e80eaff3b858c6630</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.28212547302246" miny="-11.758909225463867" maxx="40.4487419128418" maxy="-0.912709712982178"/></FeatureType><FeatureType><Name>geonode:tanzania_landcover_africover</Name><Title>Tanzania Landcover_ AFRICOVER</Title><Abstract>Original source: http://www.fao.org/geonetwork/srv/en/metadata.show?uuid=29400b68-42a5-4190-af8b-5f3e9d64d022. This dataset is a spatially re-aggregated version of the original national Africover multipurpose database. The original full resolution land cover has been produced from visual interpretation of digitally enhanced LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1997. The data was aggregated by eliminating polygons below a certain area threshold to give priority to the classes belonging to Agriculture. This threshold corresponds to approx. a 30 % reduction in the polygon count. The dataset was then re-aggregated based on area threshold values. For more information on the area thresholds used to spatially aggregate the land cover data, please see the 'spatial-agg-procedure' document available in the original FAO GeoNetwork page linked above. The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system. The data set is intended for free public access.</Abstract><Keywords>land use, land cover, features, tanzania_landcover_africover, environment, africover</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.28212547302246" miny="-11.758909225463867" maxx="40.4487419128418" maxy="-0.912709712982178"/></FeatureType><FeatureType><Name>geonode:tanzania_landcover_africover_a89cba961cf8753c588c38e3e8939d28</Name><Title>Tanzania Landcover_ AFRICOVER</Title><Abstract>Original source: http://www.fao.org/geonetwork/srv/en/metadata.show?uuid=29400b68-42a5-4190-af8b-5f3e9d64d022. This dataset is a spatially re-aggregated version of the original national Africover multipurpose database. The original full resolution land cover has been produced from visual interpretation of digitally enhanced LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1997. The data was aggregated by eliminating polygons below a certain area threshold to give priority to the classes belonging to Agriculture. This threshold corresponds to approx. a 30 % reduction in the polygon count. The dataset was then re-aggregated based on area threshold values. For more information on the area thresholds used to spatially aggregate the land cover data, please see the 'spatial-agg-procedure' document available in the original FAO GeoNetwork page linked above. The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system. The data set is intended for free public access.</Abstract><Keywords>features, tanzania_landcover_africover_a89cba961cf8753c588c38e3e8939d28</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.28212547302246" miny="-11.758909225463867" maxx="40.4487419128418" maxy="-0.912709712982178"/></FeatureType><FeatureType><Name>geonode:tanzania_national_parks_2016</Name><Title>Tanzania National Parks 2016</Title><Abstract>This dataset contains all official national parks in Tanzania. The dataset is from the national agency of Tanzania National Parks (TANAPA), and available for download through Protected Planet database: https://www.protectedplanet.net/country/TZA. Latest update was in 2016.</Abstract><Keywords>environment, features, ZanSea, national park, tanzania_national_parks_2016</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.603562819000047" miny="-11.761270708999973" maxx="39.44326539200006" maxy="-1.411639229999935"/></FeatureType><FeatureType><Name>geonode:tanzania_2022phc_wards_shapefiles</Name><Title>Tanzania Wards 2022</Title><Abstract/><Keywords>features, tanzania_2022phc_wards_shapefiles</Keywords><SRS>EPSG:3395</SRS><LatLongBoundingBox minx="29.594676576611366" miny="-11.760241218981042" maxx="40.44614003724906" maxy="-0.9847747040030813"/></FeatureType><FeatureType><Name>geonode:mwanza_tourist_facilities</Name><Title>Tourism facilities in Mwanza</Title><Abstract>This dataset contains information about tourism facilities in Mwanza City. This data was obtained from field survey in Mwanza. This dataset was produced under the Community Mapping Urban risks in Mwanza project to support local stakeholders in disaster risk management. This dataset covers the Nyamagana and Ilemea municipalities in Mwanza City.</Abstract><Keywords>hotels, mwanza_tourist_facilities, toursim, features, attractions</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="32.8683959" miny="-2.6285435" maxx="33.0603213" maxy="-2.3760351"/></FeatureType><FeatureType><Name>geonode:point_of_interest_tungamalenga</Name><Title>Tungamalenga Point of Interest</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>point_of_interest_tungamalenga, features, Research, Tungamalenga</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.0703635678504" miny="-7.864218573590343" maxx="35.11748155188307" maxy="-7.813941851723151"/></FeatureType><FeatureType><Name>geonode:tungamalenga_road</Name><Title>Tungamalenga Road Networks</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>features, Tungamalenga, tungamalenga_road</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.06934909419128" miny="-7.871956345158696" maxx="35.12138438637268" maxy="-7.812317808996844"/></FeatureType><FeatureType><Name>geonode:tungamalenga_servicepoints</Name><Title>Tungamalenga Servicepoints</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>features, tungamalenga_servicepoints, Tungamalenga</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.06939745543702" miny="-7.8715404527792705" maxx="35.1206965396733" maxy="-7.797496026061434"/></FeatureType><FeatureType><Name>geonode:tungamalenga_waterways</Name><Title>Tungamalenga Waterways</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>features, Tungamalenga, tungamalenga_waterways</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.07949092571134" miny="-7.849110579461916" maxx="35.120176685331835" maxy="-7.796518161049702"/></FeatureType><FeatureType><Name>geonode:tungamalenga_500_lschar</Name><Title>Tungamalenga_500_L</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>Tungamalenga, features, tungamalenga_500_lschar</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.06681459162393" miny="-7.877423434632104" maxx="35.12609854752434" maxy="-7.80481377342392"/></FeatureType><FeatureType><Name>geonode:tungamalenga_lulc</Name><Title>Tungamalenga_LULC</Title><Abstract>This data set was created during participatory mapping activities in Southern Highlands Tanzania. The purpose of the data was to help the analysis for the development of research papers.</Abstract><Keywords>tungamalenga_lulc, features, Tungamalenga</Keywords><SRS>EPSG:32736</SRS><LatLongBoundingBox minx="35.06677870555523" miny="-7.8774415506864734" maxx="35.12609863915747" maxy="-7.804831711384936"/></FeatureType><FeatureType><Name>geonode:unguja_shehia_corrected_update</Name><Title>Unguja Island Administrative Wards</Title><Abstract>This layer represents all Wards (Shehias in Swahili) of Unguja Island. Ward is the smallest geographical administrative unit in Zanzibar. The boundaries are officially determined by the Revolutionary Government of Zanzibar. Original data source: Tanzania National Bureau of Statistics. Access: https://www.nbs.go.tz/index.php/en/census-surveys/population-and-housing-census/173-2012-phc-shapefiles-level-three</Abstract><Keywords>unguja, unguja_shehia_corrected_update, shehia, features, wards</Keywords><SRS>EPSG:21037</SRS><LatLongBoundingBox minx="39.18132764938562" miny="-6.4783795976715695" maxx="39.58045545081221" maxy="-5.72168395982856"/></FeatureType><FeatureType><Name>geonode:unguja_island_orthophoto_infogrid</Name><Title>Unguja Island Orthophoto_ 7cm 2017</Title><Abstract>High-resolution, 3-band, true color orthophotos covering the Zanzibar Unguja island. A single image covers the area of max 3x3km. Images were mapped with drones. Spatial resolution varies between 2.5cm, 5cm, 7cm and 8cm: users are advised to check the resolution of a specific image from image properties. Drone images can be used e.g. as basemaps, reference images or for image analysis. Images were captured during Zanzibar Mapping Initiative project, in collaboration between Tanzania Commission for Science and Technology (COSTECH), Zanzibar Commission for Lands (COLA), State University of Zanzibar (SUZA), DA, Spatialinfo, OBSCOM, Sensefly/Parrot Company and The World Bank. The data can be downloaded here: https://seafile.utu.fi/d/8da39af32e6e4ba59182/</Abstract><Keywords>features, unguja_island_orthophoto_infogrid</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.17811879198595" miny="-6.502988405612319" maxx="39.58537404051361" maxy="-5.715695765796133"/></FeatureType><FeatureType><Name>geonode:zanzibar_government_forests</Name><Title>Zanzibar Government Forests</Title><Abstract>This dataset represents government owned forests in Pemba and Unguja islands of Zanzibar. Data was created during the ZEIMS (Zanzibar Environmental Information System) project.</Abstract><Keywords>features, forests, zanzibar_government_forests, environment, ZanSea</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.22043368448776" miny="-6.282451054641167" maxx="39.8762413808651" maxy="-4.88709884314647"/></FeatureType><FeatureType><Name>geonode:shehias_e00a838ff2a1068ed2992ee960f32e80</Name><Title>Zanzibar Urban West Administrative Wards</Title><Abstract>Lowest administrative areas in Zanzibar Urban West. Wards (shehias in Swahili). This dataset is part of the "Unguja Island Administrative Wards" dataset, also available in the Climate risk Database. The boundaries are officially determined by the Revolutionary Government of Zanzibar. Original data source: Tanzania National Bureau of Statistics. Access: https://www.nbs.go.tz/index.php/en/census-surveys/population-and-housing-census/173-2012-phc-shapefiles-level-three</Abstract><Keywords>administation, shehias_e00a838ff2a1068ed2992ee960f32e80, features</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.185568195417474" miny="-6.195561433579723" maxx="39.22676785912356" maxy="-6.137932845198234"/></FeatureType><FeatureType><Name>geonode:all_amenities</Name><Title>Zanzibar Urban West Amenities</Title><Abstract>This data set contains all amenities in 42 Wards in the Zanzibar Urban West in 2019. Amenities are, for example, clinics, banks, restaurants and other businesses. This data set was collected by the students of State University of Zanzibar</Abstract><Keywords>features, all_amenities</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.186004177346476" miny="-6.209567681338411" maxx="39.226652853790554" maxy="-6.137222851428813"/></FeatureType><FeatureType><Name>geonode:buildingsaoi0</Name><Title>Zanzibar Urban West Buildings</Title><Abstract>Building footprints of Zanzibar Urban West Region.</Abstract><Keywords>features, buildingsaoi0, buildings</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.1856785458722" miny="-6.197498267948469" maxx="39.2266730212205" maxy="-6.134073269929412"/></FeatureType><FeatureType><Name>geonode:drainage_point_features</Name><Title>Zanzibar Urban West Drainage Points</Title><Abstract>This shows the locations of point features directly linked to drainage. For example, the locations of water inflows into drainage lines.</Abstract><Keywords>building outflow, drainage_point_features, manhole, Drainage, pipe inflow, features, drain</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.19144339818008" miny="-6.185727776365961" maxx="39.225886383281846" maxy="-6.141743463280701"/></FeatureType><FeatureType><Name>geonode:man_made_features_b31fa061ba9e51f68f356089f42f33e7</Name><Title>Zanzibar Urban West Man-made Features</Title><Abstract>Dataset showing the locations of man made features in Urban West. These features are tagged as man made based on OpenStreetMap classification.</Abstract><Keywords>man made, man_made_features_b31fa061ba9e51f68f356089f42f33e7, water tank, features, water well, communications tower etc</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.188005882531066" miny="-6.1863295002830165" maxx="39.22428340684214" maxy="-6.134441045622351"/></FeatureType><FeatureType><Name>geonode:playgrounds</Name><Title>Zanzibar Urban West Open Areas</Title><Abstract>This shows the locations of open areas within Urban West that are predominantly used as play grounds.</Abstract><Keywords>leisure, features, open spaces, playgrounds</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.18801724209847" miny="-6.176589252526807" maxx="39.22286835125188" maxy="-6.156705808851448"/></FeatureType><FeatureType><Name>geonode:shops_f67e871ec1e882384b067ea3dd8fbc82</Name><Title>Zanzibar Urban West Retail Services</Title><Abstract>Locations of places of business in Urban West.</Abstract><Keywords>shops_f67e871ec1e882384b067ea3dd8fbc82, amenity, retail, features, shop</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.18614251109919" miny="-6.209695729857789" maxx="39.22685250716532" maxy="-6.139554816339974"/></FeatureType><FeatureType><Name>geonode:road_network</Name><Title>Zanzibar Urban West Road Network</Title><Abstract>The road network of Zanzibar Urban West categorized according to the OpenStreetMap highway classification.</Abstract><Keywords>features, road network, highway, streets, road_network, roads, paths</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.18611337174827" miny="-6.213366234423827" maxx="39.22733312695117" maxy="-6.1328871647457355"/></FeatureType><FeatureType><Name>geonode:trees_ad4fd8bef864d665041c2b4aad402a3c</Name><Title>Zanzibar Urban West Trees</Title><Abstract>The distribution of trees in Urban West as digitized from high resolution drone imagery.</Abstract><Keywords>vegetation, natural, features, tree, trees_ad4fd8bef864d665041c2b4aad402a3c, trees, urban ecology</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.189105737380046" miny="-6.202771313171629" maxx="39.22652121849624" maxy="-6.135205050047756"/></FeatureType><FeatureType><Name>geonode:water_bodies</Name><Title>Zanzibar Urban West Waterbodies</Title><Abstract>This shows the locations of waterbodies.</Abstract><Keywords>features, water_bodies</Keywords><SRS>EPSG:32737</SRS><LatLongBoundingBox minx="39.215406780291964" miny="-6.1813769821775315" maxx="39.22348964019443" maxy="-6.16366372715208"/></FeatureType><FeatureType><Name>geonode:contour_2m</Name><Title>contour_2m</Title><Abstract>Contour 2m dataset contains spatial data used for the Mwanza Master Plan. The data was collected from various sources, including field surveys, government agencies, and satellite imagery. It supports planning, infrastructure development, and urban management. Methodology included digitization, remote sensing, and validation through stakeholder engagement.</Abstract><Keywords>2m, features, contour_2m, Contour</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.8605000209857" miny="-2.662902318726787" maxx="33.03508920315421" maxy="-2.367271428229444"/></FeatureType><FeatureType><Name>geonode:district_boundaries_9a3af830e8c06df98d4319c7d480c52176b4cc56e5</Name><Title>district_boundaries_9a3af830e8c06df98d4319c7d480c542</Title><Abstract/><Keywords>features, district_boundaries_9a3af830e8c06df98d4319c7d480c52176b4cc56e5</Keywords><SRS>EPSG:21036</SRS><LatLongBoundingBox minx="32.86050831451561" miny="-2.7137055111911845" maxx="33.08198685006592" maxy="-2.363435770613485"/></FeatureType><FeatureType><Name>geonode:gadm36_tza_3</Name><Title>gadm36_tza_3</Title><Abstract/><Keywords>features, gadm36_tza_3</Keywords><SRS>EPSG:4326</SRS><LatLongBoundingBox minx="29.327167510986442" miny="-11.745695114135685" maxx="40.44513702392584" 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nArgs="1">parseBoolean</ogc:Function_Name><ogc:Function_Name nArgs="1">parseDouble</ogc:Function_Name><ogc:Function_Name nArgs="1">parseInt</ogc:Function_Name><ogc:Function_Name nArgs="1">parseLong</ogc:Function_Name><ogc:Function_Name nArgs="0">parseTime</ogc:Function_Name><ogc:Function_Name nArgs="2">pgNearest</ogc:Function_Name><ogc:Function_Name nArgs="0">pi</ogc:Function_Name><ogc:Function_Name nArgs="-1">PointBuffers</ogc:Function_Name><ogc:Function_Name nArgs="2">pointN</ogc:Function_Name><ogc:Function_Name nArgs="-1">pointOnLine</ogc:Function_Name><ogc:Function_Name nArgs="-7">PointStacker</ogc:Function_Name><ogc:Function_Name nArgs="-1">PolygonExtraction</ogc:Function_Name><ogc:Function_Name nArgs="1">polygonize</ogc:Function_Name><ogc:Function_Name nArgs="-1">PolyLabeller</ogc:Function_Name><ogc:Function_Name nArgs="2">pow</ogc:Function_Name><ogc:Function_Name nArgs="1">property</ogc:Function_Name><ogc:Function_Name nArgs="1">PropertyExists</ogc:Function_Name><ogc:Function_Name nArgs="-2">Quantile</ogc:Function_Name><ogc:Function_Name nArgs="-1">Query</ogc:Function_Name><ogc:Function_Name nArgs="-1">queryCollection</ogc:Function_Name><ogc:Function_Name nArgs="-1">querySingle</ogc:Function_Name><ogc:Function_Name nArgs="0">random</ogc:Function_Name><ogc:Function_Name nArgs="-1">RangeLookup</ogc:Function_Name><ogc:Function_Name nArgs="-1">RasterAsPointCollection</ogc:Function_Name><ogc:Function_Name nArgs="-2">RasterZonalStatistics</ogc:Function_Name><ogc:Function_Name nArgs="-6">RasterZonalStatistics2</ogc:Function_Name><ogc:Function_Name nArgs="5">Recode</ogc:Function_Name><ogc:Function_Name nArgs="-2">RectangularClip</ogc:Function_Name><ogc:Function_Name nArgs="2">relate</ogc:Function_Name><ogc:Function_Name nArgs="3">relatePattern</ogc:Function_Name><ogc:Function_Name nArgs="-1">reproject</ogc:Function_Name><ogc:Function_Name nArgs="-1">ReprojectGeometry</ogc:Function_Name><ogc:Function_Name nArgs="-3">rescaleToPixels</ogc:Function_Name><ogc:Function_Name nArgs="1">rint</ogc:Function_Name><ogc:Function_Name nArgs="1">round</ogc:Function_Name><ogc:Function_Name nArgs="1">round_2</ogc:Function_Name><ogc:Function_Name nArgs="1">roundDouble</ogc:Function_Name><ogc:Function_Name nArgs="-2">saturate</ogc:Function_Name><ogc:Function_Name nArgs="-5">ScaleCoverage</ogc:Function_Name><ogc:Function_Name nArgs="2">setCRS</ogc:Function_Name><ogc:Function_Name nArgs="2">shade</ogc:Function_Name><ogc:Function_Name nArgs="2">simplify</ogc:Function_Name><ogc:Function_Name nArgs="1">sin</ogc:Function_Name><ogc:Function_Name nArgs="1">size</ogc:Function_Name><ogc:Function_Name nArgs="-2">Snap</ogc:Function_Name><ogc:Function_Name nArgs="-3">SpatioTemporalZonalStatistics</ogc:Function_Name><ogc:Function_Name nArgs="2">spin</ogc:Function_Name><ogc:Function_Name nArgs="2">splitPolygon</ogc:Function_Name><ogc:Function_Name nArgs="1">sqrt</ogc:Function_Name><ogc:Function_Name nArgs="-2">StandardDeviation</ogc:Function_Name><ogc:Function_Name nArgs="1">startAngle</ogc:Function_Name><ogc:Function_Name nArgs="1">startPoint</ogc:Function_Name><ogc:Function_Name nArgs="1">StoreCoverage</ogc:Function_Name><ogc:Function_Name nArgs="4">strAbbreviate</ogc:Function_Name><ogc:Function_Name nArgs="1">strCapitalize</ogc:Function_Name><ogc:Function_Name nArgs="2">strConcat</ogc:Function_Name><ogc:Function_Name nArgs="2">strDefaultIfBlank</ogc:Function_Name><ogc:Function_Name nArgs="2">strEndsWith</ogc:Function_Name><ogc:Function_Name nArgs="2">strEqualsIgnoreCase</ogc:Function_Name><ogc:Function_Name nArgs="2">strIndexOf</ogc:Function_Name><ogc:Function_Name nArgs="4">stringTemplate</ogc:Function_Name><ogc:Function_Name nArgs="2">strLastIndexOf</ogc:Function_Name><ogc:Function_Name nArgs="1">strLength</ogc:Function_Name><ogc:Function_Name nArgs="2">strMatches</ogc:Function_Name><ogc:Function_Name nArgs="3">strPosition</ogc:Function_Name><ogc:Function_Name nArgs="4">strReplace</ogc:Function_Name><ogc:Function_Name nArgs="2">strStartsWith</ogc:Function_Name><ogc:Function_Name nArgs="1">strStripAccents</ogc:Function_Name><ogc:Function_Name nArgs="3">strSubstring</ogc:Function_Name><ogc:Function_Name nArgs="2">strSubstringStart</ogc:Function_Name><ogc:Function_Name nArgs="1">strToLowerCase</ogc:Function_Name><ogc:Function_Name nArgs="1">strToUpperCase</ogc:Function_Name><ogc:Function_Name nArgs="1">strTrim</ogc:Function_Name><ogc:Function_Name nArgs="3">strTrim2</ogc:Function_Name><ogc:Function_Name nArgs="-1">strURLEncode</ogc:Function_Name><ogc:Function_Name nArgs="2">StyleCoverage</ogc:Function_Name><ogc:Function_Name nArgs="2">symDifference</ogc:Function_Name><ogc:Function_Name nArgs="1">tan</ogc:Function_Name><ogc:Function_Name nArgs="2">tint</ogc:Function_Name><ogc:Function_Name nArgs="1">toDegrees</ogc:Function_Name><ogc:Function_Name nArgs="1">toRadians</ogc:Function_Name><ogc:Function_Name nArgs="2">touches</ogc:Function_Name><ogc:Function_Name nArgs="1">toWKT</ogc:Function_Name><ogc:Function_Name nArgs="2">Transform</ogc:Function_Name><ogc:Function_Name nArgs="-1">TransparencyFill</ogc:Function_Name><ogc:Function_Name nArgs="2">union</ogc:Function_Name><ogc:Function_Name nArgs="2">UnionFeatureCollection</ogc:Function_Name><ogc:Function_Name nArgs="2">Unique</ogc:Function_Name><ogc:Function_Name nArgs="-2">UniqueInterval</ogc:Function_Name><ogc:Function_Name nArgs="-4">VectorToRaster</ogc:Function_Name><ogc:Function_Name nArgs="3">VectorZonalStatistics</ogc:Function_Name><ogc:Function_Name nArgs="1">vertices</ogc:Function_Name><ogc:Function_Name nArgs="2">within</ogc:Function_Name></ogc:Function_Names></ogc:Functions></ogc:Arithmetic_Operators></ogc:Scalar_Capabilities></ogc:Filter_Capabilities></WFS_Capabilities>