WMS This is a description of your Web Map Server. WFS WMS GEOSERVER

NONE NONE text/xml image/png application/atom+xml application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html text/javascript application/json XML INIMAGE BLANK JSON JSONP This is a description of your Web Map Server. EPSG:4326 EPSG:3785 EPSG:3857 EPSG:900913 EPSG:32647 EPSG:32736 CRS:84 -179.27015693606447 40.94166666666767 -89.99859427313189 0.2939965805793807 geonode:all_amenities 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 features all_amenities EPSG:32737 CRS:84 39.186004177346476 39.226652853790554 -6.209567681338411 -6.137222851428813 other other other other other other text/xml geonode:approved_projects 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. approved_projects Projects features Approved EPSG:21036 CRS:84 32.86366662820532 33.07686014120542 -2.6450282236703178 -2.37286197787487 other other other other text/xml other other geonode:buildings 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. features urban environment buildings exposure EPSG:4326 CRS:84 32.8620827 33.08088712628851 -2.6524112 -2.3684468 other other other other text/xml other other geonode:buildingsaoi0 Building footprints of Zanzibar Urban West Region. features buildingsaoi0 buildings EPSG:32737 CRS:84 39.1856785458722 39.2266730212205 -6.197498267948469 -6.134073269929412 other other other other other other text/xml other other other other text/xml other other geonode:cbd_existing_landuse 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. cbd_existing_landuse features Urban Planning land use EPSG:21037 CRS:84 39.08493280618714 39.12690117028315 -5.0860611773503805 -5.054739664326034 other other other other text/xml other other geonode:cbd_proposed_landuse 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. cbd_proposed_landuse land use features EPSG:21037 CRS:84 39.08493271314339 39.12690117028315 -5.0860611773503805 -5.05402492861466 other other other other text/xml other other geonode:commercial_zone 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. land use features Urban commercial_zone Planning EPSG:21037 CRS:84 38.94070270787685 38.94461950922144 -5.130404351893448 -5.127631624211285 other other other other text/xml other other geonode:conservation_area 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. land use environment features conservation_area conservation EPSG:21037 CRS:84 38.897260281644584 39.139868676878386 -5.273644169828056 -4.960627880173371 other other other other text/xml other other geonode:contour_10m 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. contour_10m 10m features Contour EPSG:21036 CRS:84 32.7509627149321 33.28288806760793 -2.920023513289423 -2.3626130740553912 other other other other text/xml other other geonode:contour_2m 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. 2m features contour_2m Contour EPSG:21036 CRS:84 32.8605000209857 33.03508920315421 -2.662902318726787 -2.367271428229444 other other other text/xml other other other geonode:contours_75m 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. features Planning Urban contours_75m EPSG:4326 CRS:84 38.8543520150544 39.171240301953446 -5.26861690328993 -4.95678759799637 other other other other text/xml other other geonode:dar_es_salaam_administrative_districts 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. dar_es_salaam_administrative_districts administrative boundaries features EPSG:4326 CRS:84 39.0071592382959 39.55376584046384 -7.181490835157371 -6.56620696403837 other other other other other other text/xml other other other other other text/xml other geonode:dar_es_salaam_administrative_region 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. administrative dar_es_salaam_administrative_region features border EPSG:4326 CRS:84 39.0071592382959 39.553765922465416 -7.181490838157122 -6.566206931041475 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_administrative_subwards 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). features dar_es_salaam_administrative_subwards administrative boundaries EPSG:4326 CRS:84 39.0071592382959 39.553765922465416 -7.181490838157123 -6.566206931041475 other other other other text/xml other other other other text/xml other other other other geonode:dar_es_salaam_administrative_wards715f5b45aeaf 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. features dar_es_salaam_administrative_wards715f5b45aeaf administrative boundaries EPSG:4326 CRS:84 39.00715923800004 39.553765922000025 -7.181490837999945 -6.566206930999954 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_brt_routes_039f2af0d5edcdad6c1811f21165f4ad 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. DART features Bus Rapid Transit dar_es_salaam_brt_routes_039f2af0d5edcdad6c1811f21165f4ad BRT public transportation EPSG:4326 CRS:84 39.183274 39.2989248 -6.8264308 -6.7774908 other other other other text/xml other other geonode:dar_es_salaam_brt_stops 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. DART public transportation features dar_es_salaam_brt_stops BRT Bus Rapid Transit EPSG:4326 CRS:84 39.1866543 39.2986187 -6.8261894 -6.7777287 other other other other text/xml other other geonode:dar_es_salaam_business_areas 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. tourism features office amenity dar_es_salaam_business_areas shop EPSG:4326 CRS:84 39.0547113 39.3508568 -6.9351003 -6.6406581 other other other other other text/xml other geonode:dar_es_salaam_business_locations 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. dar_es_salaam_business_locations tourism office amenity features shop EPSG:4326 CRS:84 39.1215932 39.2811657 -6.9011741 -6.7043433 other other other other other text/xml other geonode:dar_es_salaam_canopy_cover_binary This 0.5m resolution raster datasets holds information of tree canopy cover in Dar es Salaam region. The canopy is represented as binary data - whether there is canopy (1) or is not (0). The canopy cover was mapped via remote app Groundwork by university students of UDSM, overseed by Azavea and OMDTZ during the Resilience Academy industrial training 2020. WCS natural GeoTIFF canopy trees dar_es_salaam_canopy_cover_binary environment EPSG:3857 CRS:84 39.21807809925589 39.300502153970974 -6.8698770576186 -6.741835065481061 other other other other other other text/xml other other other other text/xml other other text/plain geonode:dar_es_salaam_canopy_cover_probability This 0.5m raster layer estimates tree canopy cover in the region of Dar es Salaam. The canopy probability is higher when it is more certain that there is canopy at the raster cell location in the real world. For example, in the areas of dense forests the canopy probability is near 100 % but in the areas of small or rare trees, the canopy cover probability is lower. This layer has been produced via algorithm that was trained with canopy dataset collected by UDSM students with a remote app called Groundwork, overseed by Azavea and OMDTZ during the Resilience Academy industrial training 2020. *** Downloading via Seafile cloud service. natural WCS GeoTIFF canopy trees environment dar_es_salaam_canopy_cover_probability EPSG:3857 CRS:84 39.2180780992453 39.30050215392401 -6.869877057973639 -6.741835065887179 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_catchments 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. catchments features hydrology watershed dar_es_salaam_catchments EPSG:4326 CRS:84 38.987418958000035 39.28158562400006 -6.97219682399998 -6.723863490999975 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_crop_vegetation_management_factor_c_rusle_compre Revised Universal Soil Loss Equation (RUSLE) input crop, vegetation and management factor (C). The C factor is used to determine the relative effectiveness of soil and crop management systems in terms of preventing soil loss. The C factor was calculated from NDVI (Sentinel-2B sensor of the European Space Agency (ESA) collected on 05/06/2018). By JBA Consulting. *** This data can be downloaded through Seafile cloud service either in original size (larger) or compressed (smaller). sedimentation GeoTIFF environment RUSLE flooding WCS erosion dar_es_salaam_crop_vegetation_management_factor_c_rusle_compre geomorphology EPSG:32737 CRS:84 38.85380773003127 39.55179072591761 -7.203723614018724 -6.506111909723416 other other other other other text/xml other other text/xml other other other other other geonode:dar_es_salaam_digital_terrain_model_20m_2017 Continuous digital terrain model covering the whole Dar es Salaam area. Spatial resolution of this DTM is 5.0 meters. Vertical resolution depends on the terrain's texture (see Data Quality Statement). DTM contains elevation information about the terrain. All objects above the terrain level, such as buildings and trees, has been removed. *** Data collection and processing was conducted by COWI. DTM elevation dar_es_salaam_digital_terrain_model_20m_2017 GeoTIFF WCS EPSG:32737 CRS:84 38.69185154706161 39.5798770428223 -7.210500785730334 -6.486134838358482 other other other other text/xml other other geonode:dar_es_salaam_drain_points Drainage data of 31 out of 44 wards of the city (ongoing process). Drain points and segments traced by using ODK Collect application. drain flood Drainage features dar_es_salaam_drain_points EPSG:4326 CRS:84 39.11234038626353 39.28666 -6.896984588639111 -6.624401888812985 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_drain_segments Drainage data of 31 out of 44 wards of the city (ongoing process). Drain points and segments traced by using ODK Collect application. drain flood Drainage dar_es_salaam_drain_segments features EPSG:4326 CRS:84 39.11234038626353 39.286665 -6.896984588639111 -6.624401888812985 other text/xml other other other other other other other other other text/xml other other geonode:dar_es_salaam_education_facilities_locations0 Educational facilities in Dar es Salaam including kindergarten, primary and secondary school, college and universities that provide education services. education university kindergarten features school amenities dar_es_salaam_education_facilities_locations0 exposure EPSG:4326 CRS:84 39.0671911 39.3163149 -6.940259 -6.6336846 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_education_facilities_locations01563b83e4182 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. dar_es_salaam_education_facilities_locations01563b83e4182 retail amenity features shop EPSG:4326 CRS:84 39.0671911 39.3163149 -6.940259 -6.6336846 text/xml other other other other other other geonode:dar_es_salaam_erosion_suspectibility_model_compressed A GIS-based Erosion Susceptibility Model (ESM) was produced to support the geomorphological assessment of the watercourses within Dar es Salaam, by JBA Consulting. The ESM was developed to provide a transparent and replicable method to generate a relative estimation of erosion susceptibility across the whole of the study domain. ESM = Rainfall erosivity (used from The Global Rainfall Erosivity Database (GloREDa) provided by the European Soil Data Centre (ESDAC)) × Soil type (Calculated from the Dar es Salaam Sediment survey project produced by the Ramani Huria Project and JBA Consulting under a World Bank project 'Dar es Salaam Fluvial Geomorphology Assessment' (selection number 1256679)) × Built-up area (calculated from The Global Human Settlement Layer (GHSL) on 2018) × (2×NDVI (calculated from Sentinel-2B sensor of the European Space Agency (ESA) collected on 05/06/2018)) × Slope (calculated from the digital terrrain model (DTM) produced by COWI ). *** Data download via Seafile cloud service. File options are for the original file (larger) and compressed file (smaller). dar_es_salaam_erosion_suspectibility_model_compressed geomorphology environment flooding sedimentation GeoTIFF RUSLE erosion WCS EPSG:32737 CRS:84 38.8538077298313 39.55179072571796 -7.203723614218385 -6.506111909923278 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_flood_scenario_25___200_cm 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. flood scenario features dar_es_salaam_flood_scenario_25___200_cm winner UTU visualisation challenge EPSG:32737 CRS:84 39.09579089862734 39.47459660263135 -6.9625124436592065 -6.598532547701874 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_government_points 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. features dar_es_salaam_government_points EPSG:4326 CRS:84 39.0728248 39.2983598 -6.9142606 -6.6609069 other other other other text/xml other other geonode:dar_es_salaam_government_polygon 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. features dar_es_salaam_government_polygon EPSG:4326 CRS:84 39.1030007 39.3001779 -6.9142865 -6.7430103 other other text/xml other other other other geonode:dar_es_salaam_historical_flood_depths 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. dar_es_salaam_historical_flood_depths flood experience hazard flood depth flood features EPSG:4326 CRS:84 39.23142273 39.27407872 -6.8351383 -6.7907416667 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_historical_flood_extent 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. Flood history flood experience dar_es_salaam_historical_flood_extent hazard flood depth Flood extent Flood mitigation survey flood features EPSG:4326 CRS:84 39.23025374 39.28173 -6.83811 -6.7818033333 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_hospital_points 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. dar_es_salaam_hospital_points medicine amenities pharmacies features EPSG:4326 CRS:84 39.0854073 39.2961939 -6.9142791 -6.6530096 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_hospital_polygon 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. dispensing features emergency amenities dar_es_salaam_hospital_polygon ancillary health care EPSG:4326 CRS:84 39.1182756 39.2888625 -6.9034149 -6.7281369 other other other other other other text/xml other other other other text/xml other other geonode:dar_es_salaam_hydro_met_stations 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/. features dar_es_salaam_hydro_met_stations EPSG:4326 CRS:84 32.747035 39.2661084 -6.9107633 -2.43833 other other other other text/xml other other geonode:dar_es_salaam_hyperlocal_boundaries 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. administrative areas Hyperlocal boundaries dar_es_salaam_hyperlocal_boundaries features 'shinas' 'mjumbe' EPSG:4326 CRS:84 39.08807736961261 39.30070990521081 -6.961210707236279 -6.765797552988738 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_hyperlocal_boundaries174899b7e91f 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. 'shinas' 'mjumbe' Hyperlocal boundaries features administrative areas dar_es_salaam_hyperlocal_boundaries174899b7e91f EPSG:3857 CRS:84 39.088077369851966 39.30070990555009 -6.961210707380182 -6.765797552968433 other other other other text/xml other other geonode:dar_es_salaam_inundated_buildings 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. flood experience flooding features inundation dar_es_salaam_inundated_buildings EPSG:4326 CRS:84 39.18929059784765 39.288261397855 -6.865699895020131 -6.732785095132051 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_office_points 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. features dar_es_salaam_office_points EPSG:4326 CRS:84 39.0728248 39.3118378 -6.9154114 -6.6609069 text/xml other other other other other other geonode:dar_es_salaam_office_polygons 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. features dar_es_salaam_office_polygons EPSG:4326 CRS:84 39.097757 39.3001779 -6.9142865 -6.7430103 other other other other other text/xml other geonode:dar_es_salaam_open_areas 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). dar_es_salaam_open_areas features open areas land use EPSG:4326 CRS:84 39.1035304 39.5243562 -6.9996074 -6.6596075 other other other other text/xml other other other other other other other other text/xml geonode:dar_es_salaam_pharmacy Shops in Dar es Salaam also referred to as drugstores that sell medications as regulated and licensed by the government. dispensing dar_es_salaam_pharmacy ancillary amenities emergency features health care EPSG:4326 CRS:84 39.0619936 39.2954718 -6.9174124 -6.6615593 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_public_toilets_points 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). features dar_es_salaam_public_toilets_points EPSG:4326 CRS:84 39.1911847 39.5051137 -6.9407411 -6.6946697 other other other other other other text/xml geonode:dar_es_salaam_public_toilets_polygon 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). features dar_es_salaam_public_toilets_polygon EPSG:4326 CRS:84 39.0888066 39.2860373 -6.8982464 -6.7613156 other other other other other other text/xml geonode:dar_es_salaam_public_transportation_routes This dataset contains routes of public transportation (dala dala) routes in Dar es Salaam. bus routes dar_es_salaam_public_transportation_routes public transportation features EPSG:4326 CRS:84 39.04697107581713 39.45569682866766 -7.030666754804557 -6.577853136993972 other other other other text/xml other other geonode:dar_es_salaam_public_transportation_stops 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. Bus stops dar_es_salaam_public_transportation_stops public transportation features EPSG:4326 CRS:84 39.1320713 39.3767934 -6.8866156 -6.7007798 other other other other text/xml other other geonode:dar_es_salaam_public_water_points 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 pump dar_es_salaam_public_water_points features drinking water public water amenity EPSG:4326 CRS:84 39.1156268 39.2882895 -6.9148815 -6.7680554 other other other other other other text/xml geonode:dar_es_salaam_religious_institution_pointsdd77e5cf868c 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. amenity temple features mosque religion church denomination dar_es_salaam_religious_institution_pointsdd77e5cf868c EPSG:4326 CRS:84 39.0226415 39.3113148 -6.9711476 -6.6516709 other other other other text/xml other other geonode:dar_es_salaam_religious_institution_polygon 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. denomination features religion dar_es_salaam_religious_institution_polygon mosque church temple amenity EPSG:4326 CRS:84 39.0648846 39.3316169 -6.9400553 -6.6427373 other other other other text/xml other other geonode:dar_es_salaam_river_basins 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. features dar_es_salaam_river_basins EPSG:32737 CRS:84 38.93238375884063 39.55179067102961 -7.2036778738213885 -6.549079072168119 other other other other text/xml other other geonode:dar_es_salaam_river_channels 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. dar_es_salaam_river_channels features geomorphology environment river channels EPSG:32737 CRS:84 38.95097646408514 39.54688140364401 -7.1883890881257475 -6.568080408448569 other other other other text/xml other other geonode:dar_es_salaam_rivers Rivers in Dar es Salaam were delineated based on catchment analyses and corrected using Google Earth imagery. Used for the Msimbazi Charrette project. features dar_es_salaam_rivers EPSG:4326 CRS:84 39.008668958000044 39.28158562400006 -6.94886349099994 -6.72678015799994 other other other other other other text/xml geonode:dar_es_salaam_roads The data was collected to provide updates on all roads in Dar es Salaam for 2022. dar_es_salaam_roads roads features EPSG:4326 CRS:84 38.9708168 39.5507216 -7.4038922 -6.5755392 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_roads_442d5ed5bfa4522c77d3303f1a2ddef8 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. highway streets features roadnetwork road dar_es_salaam_roads_442d5ed5bfa4522c77d3303f1a2ddef8 paths EPSG:4326 CRS:84 38.9708168 39.5507216 -7.4038922 -6.5755392 other other other other text/xml other other other text/xml other other other other other geonode:dar_es_salaam_shops_polygon 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. retail dar_es_salaam_shops_polygon shops amenity features EPSG:4326 CRS:84 39.0547113 39.2929948 -6.9328625 -6.7091983 other other other other text/xml other other geonode:dar_es_salaam_slope_length_gradient_factor_ls_rusle_compressed Revised Universal Soil Loss Equation (RUSLE) input Slope length-gradient factor (LS). The LS factor represents a ratio of soil loss under given conditions to that at a site with the "standard" slope steepness of 9% and slope length of 22.1 m. The steeper and longer the slope, the higher the risk for erosion. The LS factor was calculated from the digital terrain model (DTM) produced by COWI (5m resolution). This dataset is produced by JBA Consulting. *** Downloading via Seafile cloud service, you may choose from the original or compressed files. dar_es_salaam_slope_length_gradient_factor_ls_rusle_compressed sedimentation environment erosion geomorphology GeoTIFF WCS RUSLE flooding EPSG:32737 CRS:84 38.85380773003127 39.55179072591761 -7.203723614018724 -6.506111909723416 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_soil_sediment_sampling 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. Soil sampling dar_es_salaam_soil_sediment_sampling flood risks soil sieving features geomorphological assessment catchment area EPSG:4326 CRS:84 38.91432 39.5450133333 -7.19723 -6.5583533333 other other other other text/xml other other other other other other text/xml other other geonode:dar_es_salaam_tourism_points 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. features dar_es_salaam_tourism_points EPSG:4326 CRS:84 39.0406632 39.5475482 -7.016678 -6.6549451 other other other other other other text/xml geonode:dar_es_salaam_tree_mapping 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. environment dar_es_salaam_tree_mapping natural trees tree species features EPSG:4326 CRS:84 39.20992666666667 39.27 -6.81 -6.78595014 other other other other text/xml other other geonode:dar_es_salaam_tree_mapping_pilot 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. features dar_es_salaam_tree_mapping_pilot EPSG:4326 CRS:84 39.25206974 39.26443167 -6.778695 -6.763203333 other other other other text/xml other other geonode:dar_es_salaam_waste_sites 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. trash environment features trash size EPSG:4326 solid waste dar_es_salaam_waste_sites EPSG:4326 CRS:84 39.043721 39.3253351714691 -6.93686674 -6.62841535714286 other other other other text/xml other other other other other other text/xml other other geonode:dar_landuselandcover Land use and land cover map of Dar es Salaam from the year 2010. features land cover dar_landuselandcover land use EPSG:6210 CRS:84 -49.48839442739898 -49.48838953045108 -6.475390795251861E-5 -5.920390774207731E-5 other other other other text/xml other other other other other other text/xml other other geonode:dar_urban_greening_project_openspaces 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. features urban greening dar_urban_greening_project_openspaces open spaces EPSG:4326 CRS:84 39.161123 39.35060129 -6.932206391 -6.752457487 other other other other text/xml other other other other other other text/xml other other geonode:dar_urban_greening_project_openspaces31aae75a18d3 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. AOI dar_urban_greening_project_openspaces31aae75a18d3 urban greening features EPSG:4326 CRS:84 39.161123 39.35060129 -6.932206391 -6.752457487 other other other other text/xml other other geonode:dar_urban_greening_project_openspacese4a5e33a6984 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. features dar_urban_greening_project_openspacese4a5e33a6984 EPSG:4326 CRS:84 39.161123 39.35060129 -6.932206391 -6.752457487 other other other text/xml other other other geonode:dar_urban_greening_project_solid_waste 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. solid waste urban greening features dar_urban_greening_project_solid_waste EPSG:4326 CRS:84 39.1652154 39.23938944 -6.8494171 -6.754483819 other other other other text/xml other other geonode:dem_masked Continuous digital terrain model covering the whole Dar es Salaam area. This is an smaller size file with 20 meter spatial resolution of, derived from the original Dar es Salaam Digital Terrain Model, 5cm 2017 (also downloadable via CRD). Vertical resolution depends on the terrain's texture. DTM contains elevation information about the terrain. All objects above the terrain level, such as buildings and trees, has been removed. *** Data collection and processing was conducted by COWI. DTM environment elevation EPSG:4326 GeoTIFF dem_masked WCS EPSG:32737 CRS:84 38.988361730373526 39.332089118334004 -6.940954225805771 -6.745860499902127 other other other other text/xml other other geonode:district_boundaries_9a3af830e8c06df98d4319c7d480c52176b4cc56e5 features district_boundaries_9a3af830e8c06df98d4319c7d480c52176b4cc56e5 EPSG:21036 CRS:84 32.86050831451561 33.08198685006592 -2.7137055111911845 -2.363435770613485 other other other other text/xml other other geonode:district_boundaries_9a3af830e8c06df98d4319c7d480c542 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. district_boundaries_9a3af830e8c06df98d4319c7d480c542 boundaries features districts EPSG:21036 CRS:84 32.86050831451561 33.08198685006592 -2.7137055111911845 -2.363435770613485 other other other other text/xml other other geonode:drainage_point_features This shows the locations of point features directly linked to drainage. For example, the locations of water inflows into drainage lines. building outflow drainage_point_features manhole Drainage pipe inflow features drain EPSG:32737 CRS:84 39.19144339818008 39.225886383281846 -6.185727776365961 -6.141743463280701 other other other other text/xml other other other other other other text/xml other other geonode:dsm_t1_t1000_reference_hazard_maps Tanzania is the most flood-affected country in East Africa, with towns and cities undergoing massive spatial expansion with a growth in informal settlements. The flooding problem is compounded by limited access to adequate municipal services and infrastructure such as water supply, sanitation, solid waste, electricity and drainage. In response to these issues, the World Bank has formed a partnership with the UK Foreign, Commonwealth and Development Office, and the establishment of the Tanzania Urban Resilience Program (TURP). This 5-year trust fund with resources from the UK's International Climate Fund for Bank executed activities to support climate resilience dialogue and training for Tanzanian cities and includes provision for recipient executed risk mitigation investments. TURP has been leading the preparation of financing for transformative flood control investments such as for Dar es Salaam's Msimbazi River, as well as establishing the Resilience Academy to foster knowledge and information on urban resilience and initiate tools to aid decision-makers and stakeholders in managing risk The dashboard and analysis that it contains provides the Government and people of Dar es Salaam and Zanzibar with the evidence-based data, information and analysis tools to help reduce the negative impacts of flooding. The dashboard is intended to allow users to access, visualize and interrogate the hazard and risk data for Dar es Salaam and Zanzibar City. flood dar es salaam dsm_t1_t1000_reference_hazard_maps GeoTIFF WCS EPSG:32737 CRS:84 38.69185154706161 39.5798770428223 -7.210500785730334 -6.486134838358482 other other other other text/xml other other other other other other text/xml other other geonode:dumping_sites 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. dumping_sites features Urban Planning EPSG:21037 CRS:84 39.07468867513488 39.08958767474465 -5.112426585415532 -4.986682064639458 other other other other text/xml other other geonode:eo4sd_mtwara_transport_2017 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. Mtwara eo4sd_mtwara_transport_2017 features road highway EPSG:32737 CRS:84 40.12167005359405 40.21001328108283 -10.322314514871378 -10.25425211085628 other other other other text/xml other other other other other other text/xml other other geonode:epza_area 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. epza_area Planning Urban features EPSG:21037 CRS:84 39.03877911294566 39.07421905143366 -5.1737448703976545 -5.127417167612568 other other other other text/xml other other geonode:existing_building_as_received_from_client 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. Existing features from buildings As existing_building_as_received_from_client Received Client EPSG:21036 CRS:84 32.862181012853874 33.03082447200341 -2.648292113282301 -2.4409745729351267 other other other other text/xml other other geonode:existing_dumping_site_99d0d83636763fbbcfdcd1bcc3f7ea96 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. features Site existing_dumping_site_99d0d83636763fbbcfdcd1bcc3f7ea96 Existing Dumping EPSG:21036 CRS:84 32.945194949729725 33.038311074143714 -2.639888081974877 -2.3947454015735223 other other other other text/xml other other geonode:existing_electricity_network 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. features Existing Network Electricity existing_electricity_network EPSG:21036 CRS:84 32.9557860796369 33.041418061673276 -2.637261862227654 -2.5414335094959166 other other other other text/xml other other geonode:existing_electricity_sub_stations 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. existing_electricity_sub_stations Stations features Existing Sub Electricity EPSG:21036 CRS:84 32.90320207180871 32.96622985841032 -2.5708082279460793 -2.4701932512892895 other other other other text/xml other other geonode:existing_ferry_route 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. existing_ferry_route features Existing Route Ferry EPSG:21036 CRS:84 31.75063333707233 34.73883582131151 -2.5429472671900477 0.2939965805793807 other other other other text/xml other other geonode:existing_ict_base_station 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. ICT features Base existing_ict_base_station Existing Station EPSG:21036 CRS:84 32.88482362812429 33.00479258704312 -2.680454679803448 -2.4482581067889115 other other other other text/xml other other geonode:existing_ict_network 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. ICT features Network Existing existing_ict_network EPSG:21036 CRS:84 32.891733986489164 32.939582971111854 -2.601314716205982 -2.4434142690129774 other other other other text/xml other other geonode:existing_landfill_site 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. Landfill features Site Existing existing_landfill_site EPSG:21036 CRS:84 32.903174145944156 32.96759095537783 -2.6393357769957544 -2.466904069972752 other other other other text/xml other other geonode:existing_landuse 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. existing_landuse features Urban Planning landuse EPSG:21037 CRS:84 38.890293775530054 39.16397257756358 -5.294944798237569 -4.961119899748001 other other other other text/xml other other geonode:existing_landuse_plan 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. features landuse Plan Existing existing_landuse_plan EPSG:21036 CRS:84 32.860506105401775 33.106590831564716 -2.732927072447428 -2.363435770613485 other other other other text/xml other other geonode:existing_natural_drainage_network 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. Drainage features Natural Existing existing_natural_drainage_network Network EPSG:21036 CRS:84 32.87441669386142 33.09482344967396 -2.7156174788404015 -2.378453813969353 other other other other text/xml other other geonode:existing_road_centreline 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. features Existing road existing_road_centreline Centreline EPSG:21036 CRS:84 32.86482330150831 33.105506030402495 -2.730594177749905 -2.373163269507682 other other other other text/xml other other geonode:existing_service_reservoir 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. Reservoir features Existing existing_service_reservoir Service EPSG:21036 CRS:84 32.889719491131665 33.03869073242205 -2.5971756181019305 -2.4808306360086534 other other other other text/xml other other geonode:existing_sewer_network 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. features Existing Service Network existing_sewer_network EPSG:21036 CRS:84 32.89133752723142 32.916678922168515 -2.5290265654710913 -2.4678436795681926 other other other other text/xml other other geonode:existing_sewerage_pump_station 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. features Site Existing existing_sewerage_pump_station Dumping EPSG:21036 CRS:84 32.89883600721918 32.90513737235382 -2.5453416364848516 -2.5066864351774645 other other other other text/xml other other geonode:existing_solid_waste_collection 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. features existing_solid_waste_collection Urban Development infrastructure Planning EPSG:21036 CRS:84 32.89453345129439 32.983402440478976 -2.6021116438766976 -2.4579826753855847 other other other other text/xml other other geonode:existing_town_planning_schemes 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. features Existing Town existing_town_planning_schemes Schemes Planning EPSG:21036 CRS:84 32.861299522944634 33.04545010919102 -2.652924785882868 -2.3745444651874217 other other other other text/xml other other geonode:existing_ward_wise_land_values 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. features Existing Ward Wise Values land existing_ward_wise_land_values EPSG:21036 CRS:84 32.86084184235208 33.157221437897206 -2.6552569336693663 -2.257940985933883 other other other other text/xml other other geonode:existing_wardwise_population_densities 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. features Existing Wardwise Population Densities existing_wardwise_population_densities EPSG:21036 CRS:84 32.86084184235208 33.157221437897206 -2.6552569336693663 -2.257940985933883 other other other other text/xml other other geonode:existing_waste_water_treatment_plant 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. features Existing water Plant Treatment Waste existing_waste_water_treatment_plant EPSG:21036 CRS:84 32.91141105234014 32.911429043623656 -2.4690692550657434 -2.4690511595698497 other other other other text/xml other other geonode:existing_waste_water_treatment_plant7d846b3e0d8e features existing_waste_water_treatment_plant7d846b3e0d8e EPSG:21036 CRS:84 32.91141105234014 32.911429043623656 -2.4690692550657434 -2.4690511595698497 other other other other text/xml other other geonode:existing_water_supply_intake 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. features Supply Existing water Intake existing_water_supply_intake EPSG:21036 CRS:84 32.88577891209987 32.899911266353726 -2.58525570888261 -2.5262058135269774 other other other other text/xml other other geonode:existing_water_supply_network 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. features Supply Existing water existing_water_supply_network Network EPSG:21036 CRS:84 32.86615139456648 33.05679179115283 -2.6475943803899296 -2.442989003767491 other other other other other other text/xml geonode:existing_water_supply_pump_stationd5e5250fc378 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. Pump features Station water Supply existing_water_supply_pump_stationd5e5250fc378 Existing EPSG:21036 CRS:84 32.88576127973253 33.02836332699394 -2.5853461552151176 -2.4882633229411684 text/xml other other other other other other geonode:existing_water_supply_zone 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. existing_water_supply_zone features Supply Existing water EPSG:21036 CRS:84 32.8612276723559 33.08188848118193 -2.713705509998235 -2.372861735163961 other other other other text/xml other other geonode:facilities 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. Planning facilities Urban features EPSG:21036 CRS:84 38.969292509443704 39.12597195974532 -5.135921225034028 -5.058072095602506 other other other other text/xml other other geonode:fd_1in200_c502335cba0d5b2aba72a4c2ff92aece The data presented here show the modelled water depth for flood events of different return periods. Both fluvial flooding (flooding from rivers) and pluvial flooding (local surface water flooding from extreme rainfall) have been simulated and can be displayed. Depths are shown in meters. Note that one would not expect all the displayed flooding to happen at the same time; rather, the data show the maximum water depth that would be expected if a flood event of the specified return period were occurring at that location. Another way of expressing this is to say that the data show the probability of experiencing a given water depth within a single year; i.e. depths shown by the ‘1-in-100 year’ layer have a 1-in-100 (or 1%) chance of occurrence in any given year. For more information about the METEOR project, please see http://meteor-project.org/. If you find data useful, please provide feedback via our questionnaire, it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 METEOR fd_1in200_c502335cba0d5b2aba72a4c2ff92aece hazard WCS GeoTIFF flood EPSG:4326 CRS:84 29.275000000001 40.94166666666767 -12.608333332899669 -0.9416666662330009 other other other other text/xml other other other other other other text/xml other other geonode:gadm36_tza_3 features gadm36_tza_3 EPSG:4326 CRS:84 29.327167510986442 40.44513702392584 -11.745695114135685 -0.98578751087183 other other other other text/xml other other geonode:hotel_sites 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. Urban features hotel_sites Planning EPSG:21037 CRS:84 39.07055757528673 39.12612813686911 -5.257405787391605 -5.061581017483083 other other other other text/xml other other geonode:improve_revelopmt_upgrading_areas_2 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. improve_revelopmt_upgrading_areas_2 Planning Urban features EPSG:21037 CRS:84 38.90494887629212 39.135982027684946 -5.253391632995279 -4.981785847427348 other other other other text/xml other other geonode:industrial_area 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. land use features Urban industrial_area Planning EPSG:21037 CRS:84 38.936238120719906 39.092723346941376 -5.174949104999944 -4.990481798466788 other other other other text/xml other other geonode:infilling_residential_developement 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. land use features Urban infilling_residential_developement Planning EPSG:21037 CRS:84 38.994640156824666 39.126706328005575 -5.128689750193409 -5.054728199145717 other other other other text/xml other other geonode:institutions 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. Planning institutions Urban features EPSG:21037 CRS:84 38.97714204506602 39.11872534279732 -5.209946178721854 -5.013088640346956 other other other other text/xml other other geonode:kahama_drain_points 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 . Drainage features kahama_drain_points Urban Infranstructure EPSG:4326 CRS:84 32.57156987 32.63436944607989 -3.856211262130192 -3.787178434723452 other other text/xml other other other other geonode:kahama_drain_segments 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 . Drainage features kahama_drain_segments EPSG:4326 CRS:84 32.57156987 32.63437722700321 -3.856211262130192 -3.787178434723452 other other other other text/xml other other geonode:kigoma_drain_points "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." infrastructure kigoma_drain_points features Drainage EPSG:4326 CRS:84 29.62086215981896 29.69759795281905 -4.921567726448054 -4.864498586574744 other other other text/xml other other other geonode:kigoma_elevation_points_c8f6a83c02e171fc81f0c9a6014dc5f0 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 elevation features Drainage EPSG:4326 urban infrastructure kigoma_elevation_points_c8f6a83c02e171fc81f0c9a6014dc5f0 EPSG:4326 CRS:84 29.6208670024909 29.697597952819 -4.92156772644805 -4.86478023751744 other other other other text/xml other other geonode:kinondoni_flood_experience 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. flood hazard Flood mitigation flood experience features kinondoni_flood_experience EPSG:4326 CRS:84 39.23521566 39.27246 -6.8196196 -6.7869736 other other other other text/xml other other other other other other text/xml other other geonode:kolekole_range_area 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. kolekole_range_area Planning Urban features EPSG:21037 CRS:84 38.97014219924319 38.992783123508715 -5.211522276987162 -5.189212826183552 other other other other text/xml other other geonode:landmark 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. landmark conservation features EPSG:21036 CRS:84 32.86510699200136 32.9907250914412 -2.7160148546541296 -2.3997698291858094 other other other other text/xml other other geonode:local_roads 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. features local_roads roads infrastructure Transportation EPSG:21037 CRS:84 38.91619495784128 39.11729893875519 -5.2595200802810265 -4.980964149596671 other other other other text/xml other other geonode:main_distribution_pipe 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. infrastructure water main_distribution_pipe features EPSG:21037 CRS:84 38.91619521731252 39.12593346163591 -5.257579026111343 -4.973799243293162 other other other other text/xml other other geonode:main_roads 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. infrastructure features Transportation roads main_roads EPSG:21037 CRS:84 38.89032704599281 39.12027422206278 -5.294903181113348 -4.969626950598672 other text/xml other other other other other geonode:main_supply_pipe 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. infrastructure water main_supply_pipe features EPSG:21037 CRS:84 38.96092533360434 39.07658831688584 -5.096076715035066 -5.055207889985431 other other other other text/xml other other geonode:man_made_features_b31fa061ba9e51f68f356089f42f33e7 Dataset showing the locations of man made features in Urban West. These features are tagged as man made based on OpenStreetMap classification. man made man_made_features_b31fa061ba9e51f68f356089f42f33e7 water tank features water well communications tower etc EPSG:32737 CRS:84 39.188005882531066 39.22428340684214 -6.1863295002830165 -6.134441045622351 other other other other text/xml other other other other other other text/xml other other geonode:mini_bus_stand_pongwe 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. Planning mini_bus_stand_pongwe Urban features EPSG:21037 CRS:84 38.97812181751617 38.97897845559967 -5.1223922892413345 -5.1213016191246155 other other other other text/xml other other geonode:minor_roads 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. minor_roads infrastructure features Transportation roads EPSG:21037 CRS:84 38.93477233106756 39.13422305368483 -5.259237404622834 -4.985255133731865 other other other other text/xml other other geonode:mismbazi_dtm_lidar_050m_2019_output UNDER REVISE A Digital Elevation Model of the Msimbazi River. It has a spatial resolution of 0.50 cm and is based on imagery collected with a photogrammetric drone. Horizontal datum: WGS84 UTM 37S Vertical datum: WGS84 ellipsoid Processing was conducted by CDR International and Shore monitoring. UAV elevation GeoTIFF hydrology DEM WCS mismbazi_dtm_lidar_050m_2019_output EPSG:32737 CRS:84 39.253932646722326 39.286246114224845 -6.824075653604734 -6.791071611636702 other other other other text/xml other other geonode:morogoro_drain_points 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. urban infrastructure Drainage features morogoro_drain_points EPSG:4326 CRS:84 37.62601208165365 37.71545253833334 -6.858604671666665 -6.770783814334636 other other other other text/xml other other geonode:morogoro_drain_points_f02d30ec5bbb013a6242b4e29221fa62 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. urban infrastructure Drainage morogoro_drain_points_f02d30ec5bbb013a6242b4e29221fa62 features EPSG:4326 CRS:84 37.62601208165365 37.71545253833334 -6.858604671666665 -6.770783814334636 other other other other text/xml other other geonode:morogoro_drain_segments 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. morogoro_drain_segments features Morogoro_drain_segments EPSG:4326 CRS:84 37.62601208165365 37.71545253833334 -6.858604671666665 -6.770783814334636 text/xml other other other other other other other other other other text/xml other other geonode:morogoro_tree_mapping_f749cf095b21d14514abfc90ed3f8f87 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. environment natural trees morogoro_tree_mapping_f749cf095b21d14514abfc90ed3f8f87 tree species features EPSG:4326 CRS:84 37.62473167 37.633405 -6.799143333 -6.792005 text/xml other other other other other other geonode:msimbazi_charrette_boundary_20180706 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. features Msimbazi Charrette msimbazi_charrette_boundary_20180706 EPSG:32737 CRS:84 39.115464014293295 39.28612953296545 -6.884581323379906 -6.78615554860956 other other other other text/xml other other other other other other text/xml other other geonode:msimbazi_dem_lidar_1_0m_2019_output A Digital Elevation Model of the Msimbazi River. It has a spatial resolution of 1 m and is based on data collected with a LiDAR drone. Horizontal datum: WGS84 UTM 37S Vertical datum: WGS84 ellipsoid Processing was conducted by CDR International and Shore monitoring. elevation UAV WCS GeoTIFF DEM msimbazi_dem_lidar_1_0m_2019_output hydrology EPSG:32737 CRS:84 39.25392812185641 39.2862461169111 -6.824080178957556 -6.791071611636702 other other other other text/xml other other geonode:msimbazi_dem_uav_0_5m_2019_output A Digital Elevation Model of the Msimbazi River. It has a spatial resolution of 0.50 cm and is based on imagery collected with a photogrammetric drone. Horizontal datum: WGS84 UTM 37S Vertical datum: WGS84 ellipsoid Processing was conducted by CDR International and Shore monitoring. msimbazi_dem_uav_0_5m_2019_output UAV elevation GeoTIFF hydrology DEM WCS EPSG:32737 CRS:84 39.25393511490979 39.28623952706303 -6.824069286390044 -6.7910742955458 other other other other text/xml other other geonode:msimbazi_valley_drone_imagery_5cm_2016_optimized Drone images for lower Msimbazi Valley GeoTIFF WCS msimbazi_valley_drone_imagery_5cm_2016_optimized UAV imagery EPSG:32737 CRS:84 39.25915067316666 39.28604469776332 -6.820878001943266 -6.790707305065316 other other other other text/xml other other geonode:mtwara_final_buildings 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. mtwara_final_buildings features Mtwara buildings Tanzania EPSG:4326 CRS:84 40.1461388 40.2083046 -10.3091371 -10.2537399 other other text/xml other other other other geonode:mtwara_waste_collection_points 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. features solid waste Mtwara mtwara_waste_collection_points Tanzania EPSG:4326 CRS:84 40.1557373475352 40.1954184139549 -10.3071952955985 -10.261741948705 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_businesses 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. exposure features mwanza_businesses shops businesses EPSG:4326 CRS:84 32.8787971 32.9739866 -2.6340095 -2.4463882 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_businesses_1ee0de54004d225e705484644af28018 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. features mwanza_businesses_1ee0de54004d225e705484644af28018 shops businesses exposure EPSG:4326 CRS:84 32.8787971 32.9739866 -2.6340095 -2.4463882 other other other other text/xml other other geonode:mwanza_drainage_points 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. mwanza_drainage_points exposure Drainage features urban infrastructure EPSG:4326 CRS:84 32.88218822264999 32.96732693110052 -2.5754822 -2.443082078303363 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_drainage_points_elevation 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. mwanza_drainage_points_elevation exposure elevation Drainage features urban infrastructure EPSG:4326 CRS:84 32.8824926 32.96770325 -2.575306225 -2.443109675 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_financial_amenities 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. exposure mwanza_financial_amenities amenities features finance EPSG:4326 CRS:84 32.8891182 32.9534071 -2.6218129 -2.4540071 other other other other text/xml other other geonode:mwanza_health_facilities 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. amenities features exposure health clinic mwanza_health_facilities EPSG:4326 CRS:84 32.8796422 32.9555074 -2.6339578 -2.4503072 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_households_affected_by_rockfall 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. disaster urban environment features hazard mwanza_households_affected_by_rockfall rockfall EPSG:4326 CRS:84 32.88399836 32.92547333 -2.58806 -2.47462 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_households_at_risk_of_rockfall 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. disaster mwanza_households_at_risk_of_rockfall urban environment features hazard rockfall EPSG:4326 CRS:84 32.88079669455472 32.9763620875604 -2.634122440927163 -2.473718068389893 other other other text/xml other other other other other other other text/xml other other geonode:mwanza_offices 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. features mwanza_offices office exposure EPSG:4326 CRS:84 32.8801703 33.0180519 -2.6267154 -2.4532151 other other other other text/xml other other geonode:mwanza_other_points_of_interest 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. mwanza_other_points_of_interest exposure gas station amenities features library POI bar urban infrastructure EPSG:4326 CRS:84 32.8761231 32.9949409 -2.6285435 -2.3992216 other other other text/xml other other other other other other other other other text/xml geonode:mwanza_religious_facilities 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. religion exposure mosque features christian mwanza_religious_facilities muslim church EPSG:4326 CRS:84 32.882638 33.0188522 -2.6220272 -2.446665 text/xml other other other other other other other other other other text/xml other other geonode:mwanza_roads 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. mwanza_roads exposure infrastructure features roads EPSG:4326 CRS:84 32.8636547 33.08086004297584 -2.655194983069022 -2.375680139182044 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_rockfall_locations 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. urban environment disaster mwanza_rockfall_locations rockfall features hazard EPSG:4326 CRS:84 32.88093333 32.97423363 -2.633896982 -2.4739638 other other other other text/xml other other other other other other text/xml other other geonode:mwanza_tourist_facilities 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. hotels mwanza_tourist_facilities toursim features attractions EPSG:4326 CRS:84 32.8683959 33.0603213 -2.6285435 -2.3760351 other other other other text/xml other other geonode:new_cbd_boundary 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. administation new_cbd_boundary boundaries features EPSG:21037 CRS:84 39.08441590292169 39.12713818354688 -5.086201156421791 -5.053177967324989 other text/xml other other other other other geonode:new_residential_develepment 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. land use features Urban new_residential_develepment Planning EPSG:21037 CRS:84 38.91392324344273 39.120705362865515 -5.258925994366911 -4.980963534317337 other other other other text/xml other other geonode:ningwi_community_heritage 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. features tourism culture recreation ningwi_community_heritage EPSG:4326 CRS:84 39.295001 39.300357 -5.729321 -5.722976 other other other other text/xml other other geonode:nungwi_art_centers 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. art art centers nungwi_art_centers features EPSG:4326 CRS:84 39.290923708252244 39.29866655718065 -5.736431885099842 -5.725709916598728 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_buildings 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. infrastructure buildings features nungwi_buildings EPSG:4326 CRS:84 39.28919876472999 39.31302874892266 -5.743631106310066 -5.72221279493769 other other other other text/xml other other text/xml other other other other other other geonode:nungwi_businesses 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. businesses features shops nungwi_businesses EPSG:4326 CRS:84 39.290430622992794 39.30997697542842 -5.742573892337434 -5.722545916011199 text/xml other other other other other other geonode:nungwi_community_centers_0ef07a3eeb1f5579c71a6d94efe298d3 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. social communication features nungwi_community_centers_0ef07a3eeb1f5579c71a6d94efe298d3 community EPSG:4326 CRS:84 39.29432212480359 39.303275992566526 -5.737855912112262 -5.723916883781329 other other other other text/xml other other geonode:nungwi_craft_workshops 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. crafts features painting nungwi_craft_workshops arts EPSG:4326 CRS:84 39.29208442143086 39.301865996896574 -5.739123875928084 -5.722900948533137 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_dining_and_recreation 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. amenities dining features tourism nungwi_dining_and_recreation recreation EPSG:4326 CRS:84 39.28823361330242 39.309598425367696 -5.750087006370434 -5.722718158654486 other other other other text/xml other other geonode:nungwi_education_facilities 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. nungwi_education_facilities education amenities features EPSG:4326 CRS:84 39.29344240464585 39.3028329434684 -5.741666945566855 -5.723248919519572 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_health_facilities 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. health amenities features clinic nungwi_health_facilities EPSG:4326 CRS:84 39.29304058821926 39.29845599207806 -5.733819610387461 -5.727041011899185 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_hotels 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. hotels tourism accommodation features recreation nungwi_hotels EPSG:4326 CRS:84 39.291616848325475 39.311463417729044 -5.735903817940202 -5.723425473485442 other other other other text/xml other other geonode:nungwi_information_signs 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. nungwi_information_signs infrastructure communication features information EPSG:4326 CRS:84 39.28811305939129 39.306351 -5.750708551275962 -5.722488 other other other other text/xml other other geonode:nungwi_inland_waters 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. features nungwi_inland_waters EPSG:4326 CRS:84 39.30278479376918 39.30370942969111 -5.724133102742839 -5.722254345834618 text/xml other other other other other other geonode:nungwi_landuse 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. features nungwi_landuse land use EPSG:4326 CRS:84 39.28873231165042 39.31319583827833 -5.742957927037354 -5.72191385596687 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_playgrounds 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. features nungwi_playgrounds playgrounds open spaces EPSG:4326 CRS:84 39.290067523954946 39.311095377957145 -5.73619135897113 -5.725433453829729 other other other other text/xml other other geonode:nungwi_protected_areas 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. biodiversity lighthouse conservation features nungwi_protected_areas EPSG:4326 CRS:84 39.30249984816104 39.30403336218257 -5.723469876069896 -5.721921301361488 other other other other text/xml other other other other other text/xml other other other geonode:nungwi_religious_facilities 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. amenities nungwi_religious_facilities religion features EPSG:4326 CRS:84 39.29240386234588 39.30143669202229 -5.741404612709577 -5.724379354498963 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_roads 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. exposure highways infrastructure features nungwi_roads road EPSG:4326 CRS:84 39.284652479422284 39.32270538435216 -5.840222212560735 -5.722209475119807 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_solid_waste_management 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. trash waste management amenities features sanitation nungwi_solid_waste_management EPSG:4326 CRS:84 39.29269392835113 39.30891974817053 -5.741849908138914 -5.723421877020718 other other other other text/xml other other geonode:nungwi_street_lighting 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. infrastructure features utilities lighting nungwi_street_lighting EPSG:4326 CRS:84 39.289962960055874 39.29802318377416 -5.73620190601272 -5.724906538482586 other other other other text/xml other other other other other other text/xml other other geonode:nungwi_swimming_pools 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. swimming pools water features nungwi_swimming_pools leisure hotels EPSG:4326 CRS:84 39.289592045675064 39.31263365304967 -5.741440901350514 -5.722855452182504 other other other other other text/xml other other other other other other text/xml other geonode:nungwi_toilets 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. amenities toilets features sanitation WC nungwi_toilets EPSG:4326 CRS:84 39.29374899965233 39.30471069190679 -5.741565587673103 -5.72315578166006 other other other other text/xml other other geonode:nungwi_tourist_attractions 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. features zoo nungwi_tourist_attractions conservation tourist attractions EPSG:4326 CRS:84 39.30270592168722 39.30483541185911 -5.724638222781489 -5.722313224297604 other other other other text/xml other other geonode:nungwi_trees 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. urban ecology features nungwi_trees trees EPSG:4326 CRS:84 39.2888393472985 39.318484470326666 -5.744897517876384 -5.722131442971923 other other other other text/xml other other geonode:nungwi_useful_services 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. utilities nungwi_useful_services amenities features infrastructure POI EPSG:4326 CRS:84 39.291411223956935 39.30116019057784 -5.742866345940455 -5.726635212290615 other other other text/xml other other other geonode:nungwi_water_points 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. features water nungwi_water_points amenities EPSG:4326 CRS:84 39.29391276252863 39.30386097547955 -5.742715918265483 -5.72401493761567 other other other other text/xml other other geonode:nungwi_water_points_0255c1114173fd8aa80c2dadab1312c2 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. nungwi_water_points_0255c1114173fd8aa80c2dadab1312c2 features drinking water watershed public water EPSG:4326 CRS:84 39.29391276252863 39.30386097547955 -5.742715918265483 -5.72401493761567 other other text/xml other other other other geonode:ocean_area 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. Planning ocean_area Urban features EPSG:21037 CRS:84 38.89801421967739 39.16395321531942 -5.220900787128129 -4.969493595121327 other other other other text/xml other other geonode:ocean_line_boundary       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. administrative boundaries features ocean_line_boundary EPSG:32737 CRS:84 39.04639432452377 39.136857018350824 -5.257384195431794 -4.968520480298928 other other other other text/xml other other geonode:oil_proposed_2 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. Planning Urban features oil_proposed_2 EPSG:21037 CRS:84 39.084927495673305 39.126854907252024 -5.072738637724738 -5.013780548457788 other other other other text/xml other other geonode:output_19017_hazard_map_mean_24306de437f136381 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. METEOR hazard features output_19017_hazard_map_mean_24306de437f136381 earthquake EPSG:4326 CRS:84 29.34517 40.43317 -11.72812 -1.00012 other other other other text/xml other other other other other other text/xml other other geonode:output_merged_optimized Satellite images of Dar es Salaam (Planet, 2018). WCS GeoTIFF Satellite imgaery output_merged_optimized EPSG:3857 CRS:84 38.847656244660726 39.63867186955086 -7.362466864463051 -6.402648405022478 other other other other text/xml other other geonode:output_merged_optimized_29ea40be8e800a47850194cd464a7d50 Satellite images of Dar es Salaam (Planet, 2017) q3 L16 mosaic Satellite imgaery WCS GeoTIFF output_merged_optimized_29ea40be8e800a47850194cd464a7d50 EPSG:3857 CRS:84 38.847656244660726 39.63867186955086 -7.362466864463051 -6.402648405022478 other other other other text/xml other other geonode:pemba_island_orthophoto_infogrid 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 features pemba_island_orthophoto_infogrid EPSG:4326 CRS:84 39.560167005065125 39.88478399923173 -5.501198844314135 -4.849804598867014 other other other other text/xml other other geonode:pipe_diameter_150_300 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. infrastructure water pipe_diameter_150_300 features EPSG:21037 CRS:84 38.917962254684205 39.12525094628104 -5.224678172289908 -4.997971908725417 other other other other text/xml other other geonode:pipeline_buffer_30m 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. infrastructure water pipeline_buffer_30m features EPSG:21037 CRS:84 38.757032105231914 39.1288722562584 -5.211334759055315 -5.010410924471791 other other other other text/xml other other geonode:place_name 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. name Place place_name features EPSG:21036 CRS:84 32.880554445140135 33.200935320428066 -2.717321990637775 -2.3839728866539285 other other other other text/xml other other geonode:playgrounds This shows the locations of open areas within Urban West that are predominantly used as play grounds. leisure features open spaces playgrounds EPSG:32737 CRS:84 39.18801724209847 39.22286835125188 -6.176589252526807 -6.156705808851448 other other other other text/xml other other other other other other text/xml other other geonode:point_of_interest_tungamalenga 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. point_of_interest_tungamalenga features Research Tungamalenga EPSG:32736 CRS:84 35.0703635678504 35.11748155188307 -7.864218573590343 -7.813941851723151 text/xml other other other other other other geonode:potentials 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. potentials Planning Urban features EPSG:21037 CRS:84 39.02983925692507 39.12921141814753 -5.089752072451671 -5.041221816905463 other other other other text/xml other other geonode:powerline 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. Urban powerline Planning features EPSG:21037 CRS:84 38.873928956187484 39.07086211780306 -5.147047818548188 -5.082322163416569 other other other other text/xml other other geonode:powerline_buffer_60m 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. powerline_buffer_60m Planning Urban features EPSG:21037 CRS:84 38.873716705841645 39.07099500856137 -5.147216291251586 -5.082085672420776 other other other other text/xml other other geonode:proposed_bus_rapid_transit_network 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. Bus features Proposed Transit Rapid proposed_bus_rapid_transit_network Network EPSG:21036 CRS:84 32.89467008410617 32.99534787127501 -2.6246104584889043 -2.4413662533729688 other other other other text/xml other other geonode:proposed_drainage_catchment 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. Drainage features proposed_drainage_catchment Proposed catchments EPSG:21036 CRS:84 32.86050955411963 33.081986121481314 -2.7028594752063464 -2.363435842085926 other other other other other other text/xml geonode:proposed_drainage_channel 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 features Centre water Distribution proposed_drainage_channel Proposed EPSG:21036 CRS:84 32.89460203456525 33.08161203152701 -2.655839431381393 -2.383665412410907 other other other other text/xml other other geonode:proposed_drainage_channel_391e6b761af320bb4c37be924ed17b83 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 Drainage features Channel Proposed proposed_drainage_channel_391e6b761af320bb4c37be924ed17b83 EPSG:21036 CRS:84 32.89460203456525 33.08161203152701 -2.655839431381393 -2.383665412410907 other other other other text/xml other other geonode:proposed_drainage_detention_pond 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. Drainage proposed_drainage_detention_pond features Proposed ponds detetion EPSG:21036 CRS:84 32.89790631642361 32.9049103931403 -2.498419100235235 -2.4871092134797563 other other other other text/xml other other geonode:proposed_drainage_natural_wetland features proposed_drainage_natural_wetland EPSG:21036 CRS:84 32.88482625156908 33.01659496312965 -2.6583616855013705 -2.387899079916215 other other other other text/xml other other geonode:proposed_drainage_natural_wetlandf040fff6db3d 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. natural Proposed features proposed_drainage_natural_wetlandf040fff6db3d Natural Drainage Wetland EPSG:21036 CRS:84 32.88482625156908 33.01659496312965 -2.6583616855013705 -2.387899079916215 other other other other text/xml other other geonode:proposed_drainage_network 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. Drainage features proposed_drainage_network Proposed Network EPSG:21036 CRS:84 32.8743155954656 33.08108354926608 -2.6550393540378585 -2.387934840660068 other other other other text/xml other other geonode:proposed_electric_sub_station 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. proposed_electric_sub_station features Proposed Station Electric Sub EPSG:21036 CRS:84 32.90305870314411 33.024839524116516 -2.635993771563483 -2.439635201383949 other other other other text/xml other other geonode:proposed_electricity_network 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. features Electricity Network proposed_electricity_network Proposed EPSG:21036 CRS:84 32.90120199476456 33.035842468261926 -2.6795693898590307 -2.4218245530620868 other other other other text/xml other other geonode:proposed_environment_treatment_zone 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. Zone proposed_environment_treatment_zone environment features Proposed Treatment EPSG:21036 CRS:84 32.94620444905341 32.95780891036206 -2.6461194428173163 -2.49019712318336 other other other other text/xml other other geonode:proposed_ict_network 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. proposed_ict_network Proposed ICT features Network EPSG:21036 CRS:84 32.872937023708985 33.06034965125732 -2.7051342431190157 -2.3846127927136793 other other other other text/xml other other geonode:proposed_ict_shape 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. Proposed Shape ICT features proposed_ict_shape EPSG:21036 CRS:84 32.87438090699422 33.04611272029279 -2.669879547254124 -2.385115604810179 other other other other text/xml other other geonode:proposed_planning_district_boundaries 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. boundaries features Proposed districts proposed_planning_district_boundaries Planning EPSG:21036 CRS:84 32.8612276723559 33.08188848118193 -2.713705509998235 -2.372861735163961 other other other other text/xml other other geonode:proposed_planning_zone_boundaries569743b61cdd 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. Zone boundaries features Proposed proposed_planning_zone_boundaries569743b61cdd Planning EPSG:21036 CRS:84 32.8612276723559 33.08188848118193 -2.713705509998235 -2.372861735163961 other other other other text/xml other other geonode:proposed_road_right_of_way 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. features Proposed road Way proposed_road_right_of_way Right EPSG:21036 CRS:84 32.863075666730175 33.092512124801196 -2.731803411716374 -2.373347547422056 other other other other text/xml other other geonode:proposed_roads 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. infrastructure features Transportation roads proposed_roads EPSG:21037 CRS:84 38.75158079727286 39.07228449954223 -5.230201209974397 -4.958745523886766 other other other other text/xml other other geonode:proposed_sewer_network 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. proposed_sewer_network features Proposed Sewer Network EPSG:21036 CRS:84 32.866089314333564 33.02247413353412 -2.654393372370855 -2.37381615472539 other other other other text/xml other other geonode:proposed_sewerage_constructed_wetland 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. Sewerage proposed_sewerage_constructed_wetland features Proposed Wetland Constructed EPSG:21036 CRS:84 32.92503000095809 33.02615582714554 -2.645665655266574 -2.480010049622866 other other other other text/xml other other geonode:proposed_sewerage_transfer_station 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 Sewerage features Proposed Station Transfer proposed_sewerage_transfer_station EPSG:21036 CRS:84 32.951957955718065 32.99284937484352 -2.639475861897017 -2.4213066900291347 other other other other text/xml other other geonode:proposed_sewerage_zones 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. Zone Sewerage features Proposed proposed_sewerage_zones EPSG:21036 CRS:84 32.8612276723559 33.08188848118193 -2.713705509998235 -2.372861735163961 other other other other other text/xml other geonode:proposed_small_center 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. Planning proposed_small_center Urban features EPSG:21037 CRS:84 38.92362191537243 39.11383410117386 -5.2558583001973584 -4.98791839266763 other other other other text/xml other other geonode:proposed_soild_waste_landfill 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. Landfill features solid Proposed Waste proposed_soild_waste_landfill EPSG:21036 CRS:84 33.00020627037779 33.04460675139108 -2.616685735523873 -2.432456540612442 text/xml other other other other other other geonode:proposed_solid_waste_collection_zone 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. Zone proposed_solid_waste_collection_zone solid features Proposed Waste Collection EPSG:21036 CRS:84 32.86123427446807 33.08188458531649 -2.6551215175396345 -2.372861735163961 other other other other text/xml other other geonode:proposed_solid_waste_transfer_station 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. features solid Proposed Station proposed_solid_waste_transfer_station Transfer Waste EPSG:21036 CRS:84 32.951957955718065 32.99284937484352 -2.639475861897017 -2.4213066900291347 other other other text/xml other other other geonode:proposed_stp_pumping_station_transfer_station 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. STP features Proposed Station Pumping Transfer proposed_stp_pumping_station_transfer_station EPSG:21036 CRS:84 32.86608933733921 33.009148026886024 -2.6541793889606526 -2.3742910638140047 other other other other text/xml other other geonode:proposed_urban_design_planning_boundary 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. features proposed_urban_design_planning_boundary Proposed boundary Urban Planning Design EPSG:21036 CRS:84 32.8905762184764 32.90849026615983 -2.5269717073225784 -2.505279905702135 other other other other text/xml other other geonode:proposed_water_distribution_centre 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. features Centre water Distribution proposed_water_distribution_centre Proposed EPSG:21036 CRS:84 32.872382233709885 33.05249665546979 -2.633788558707121 -2.4187204428878646 other other other other text/xml other other geonode:proposed_water_supply_intake 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. features Supply Intake water Proposed proposed_water_supply_intake EPSG:21036 CRS:84 32.980032799414545 32.98005078861393 -2.3805621047710694 -2.3805440101719477 other other other other text/xml other other geonode:proposed_water_supply_network 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. features proposed_water_supply_network water Supply Network Proposed EPSG:21036 CRS:84 32.87274664563247 33.05579624868077 -2.6382542473007766 -2.382586113186085 other other other other text/xml other other geonode:proposed_water_supply_zone 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. Zone features Supply Proposed water proposed_water_supply_zone EPSG:21036 CRS:84 32.8612276723559 33.08188848118193 -2.713705509998235 -2.372861735163961 other other other other text/xml other other geonode:quarry_sites 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. Planning Urban features quarry_sites EPSG:21037 CRS:84 39.00063284915415 39.04258408863813 -5.0975263809347835 -5.060061902515855 other other other other text/xml other other geonode:regional_boundaries 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. regional_boundaries Regional boundaries features EPSG:21036 CRS:84 31.93248364460408 33.79105337096991 -3.437801345910545 -1.669479609380604 other other other other text/xml other other geonode:rivers 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. features rivers Urban Planning EPSG:21036 CRS:84 38.915887479087154 39.127579630918405 -5.106527565732776 -5.015484574690533 other other other other text/xml other other geonode:road_network The road network of Zanzibar Urban West categorized according to the OpenStreetMap highway classification. features road network highway streets road_network roads paths EPSG:32737 CRS:84 39.18611337174827 39.22733312695117 -6.213366234423827 -6.1328871647457355 other other other other text/xml other other other other other other text/xml other other geonode:rural_settlement_agriculture 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. rural_settlement_agriculture Planning Urban features EPSG:21037 CRS:84 38.89022059508975 39.11762875606704 -5.294945061359291 -4.9626380401839265 other other other other text/xml other other geonode:service_industries 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. Planning Urban features service_industries EPSG:21037 CRS:84 38.94444785587134 39.11423093616111 -5.129757937216599 -5.007691295088284 other other other other text/xml other other geonode:shehias_e00a838ff2a1068ed2992ee960f32e80 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 administation shehias_e00a838ff2a1068ed2992ee960f32e80 features EPSG:32737 CRS:84 39.185568195417474 39.22676785912356 -6.195561433579723 -6.137932845198234 other other other other text/xml other other other other other other text/xml other other geonode:shops features shops EPSG:32737 CRS:84 39.18614251109919 39.22685250716532 -6.209695729857789 -6.139554816339974 other other other other text/xml other other geonode:shops_f67e871ec1e882384b067ea3dd8fbc82 Locations of places of business in Urban West. shops_f67e871ec1e882384b067ea3dd8fbc82 amenity retail features shop EPSG:32737 CRS:84 39.18614251109919 39.22685250716532 -6.209695729857789 -6.139554816339974 other other other other text/xml other other geonode:shore_msimbaziriver_surveydata_cd_february2019 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. elevation features EPSG:4326 shore_msimbaziriver_surveydata_cd_february2019 hydrology survey data EPSG:32737 CRS:84 39.25455615802744 39.28836374173562 -6.818621644608205 -6.793262237284131 other other other other text/xml other other geonode:sisal_estate 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. Planning sisal_estate Urban features EPSG:21037 CRS:84 38.96621741290712 39.03902107005745 -5.249421923432712 -5.101049124505692 other other other other text/xml other other geonode:sisal_farms 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. sisal_farms Planning Urban features EPSG:21037 CRS:84 39.01369064497751 39.07089821274713 -5.0718675955244406 -5.051613100220284 other other other other text/xml other other geonode:special_residential 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. special_residential land use features Urban Planning EPSG:21037 CRS:84 39.08741123950544 39.09354974959193 -5.0793188713715 -5.068568272853546 other other other other text/xml other other geonode:storage_tanks 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. storage_tanks Planning Urban features EPSG:21037 CRS:84 38.90880584806131 39.07185578261031 -5.173058267807176 -5.055563427928354 other other other other other text/xml other geonode:sumbawanga_drain_elevations 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. sumbawanga_drain_elevations elevation features Drainage urban infrastructure EPSG:4326 CRS:84 31.57911806 31.6541043666667 -8.02185935 -7.92531528833333 other text/xml other other other other other geonode:sumbawanga_drain_pointsgpkg_shm 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. urban infrastructure Drainage features sumbawanga_drain_pointsgpkg_shm EPSG:4326 CRS:84 31.57911806000001 31.65410436666667 -8.02185935 -7.925315288333333 other other other other text/xml other other geonode:tanga_city_boundary 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. administrative tanga_city_boundary boundaries features EPSG:21037 CRS:84 38.89022216440866 39.164051887091645 -5.295042003726771 -4.961101803304519 other other other text/xml other other other geonode:tanga_oil_sites 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. Urban Planning tanga_oil_sites features EPSG:21037 CRS:84 39.07939706834035 39.13280582209286 -5.072739340313304 -4.9875804270017445 other other other other text/xml other other geonode:tanga_port 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. tanga_port Planning Urban features EPSG:21037 CRS:84 39.10095842022406 39.1189866579594 -5.128621830213495 -5.063650606396815 other other other other text/xml other other geonode:tanzania_2022phc_wards_shapefiles features tanzania_2022phc_wards_shapefiles EPSG:3395 CRS:84 29.594676576611366 40.44614003724906 -11.760241218981042 -0.9847747040030813 other other other other text/xml other other geonode:tanzania_coralreef_2018 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). ZanSea tanzania_coralreef_2018 features coral reef environment EPSG:4326 CRS:84 38.7960069560562 40.46147214702199 -10.371064700575403 -4.70216632691438 other other other other text/xml other other other other other other text/xml other other geonode:tanzania_forest_reserves_2020 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. environment tanzania_forest_reserves_2020 features ZanSea forests forest TFS EPSG:4326 CRS:84 29.737066269000024 40.43065642000005 -11.620379343999957 -1.000471433999962 other other other other text/xml other other other other other other other text/xml other geonode:tanzania_landcover_africover 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. land use land cover features tanzania_landcover_africover environment africover EPSG:4326 CRS:84 29.28212547302246 40.4487419128418 -11.758909225463867 -0.912709712982178 other other other other text/xml other other other other other other text/xml other other geonode:tanzania_landcover_africover_a89cba961cf8753c588c38e3e8939d28 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. features tanzania_landcover_africover_a89cba961cf8753c588c38e3e8939d28 EPSG:4326 CRS:84 29.28212547302246 40.4487419128418 -11.758909225463867 -0.912709712982178 other other other other text/xml other other geonode:tanzania_landcover_africover_cb4fe9bf1d2e748e80eaff3b858c6630 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. features tanzania_landcover_africover_cb4fe9bf1d2e748e80eaff3b858c6630 EPSG:4326 CRS:84 29.28212547302246 40.4487419128418 -11.758909225463867 -0.912709712982178 other other other other text/xml other other geonode:tanzania_national_parks_2016 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. environment features ZanSea national park tanzania_national_parks_2016 EPSG:4326 CRS:84 29.603562819000047 39.44326539200006 -11.761270708999973 -1.411639229999935 other other other other text/xml other other other other other other text/xml other other geonode:tipper_oil_storage 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. Urban tipper_oil_storage Planning features EPSG:21037 CRS:84 39.11941243147539 39.13279331281516 -5.011123662115468 -5.008027805919125 other other other other text/xml other other geonode:tourist_attraction_sites 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. Planning tourist_attraction_sites Urban features EPSG:21037 CRS:84 39.0247138657871 39.164032354177714 -5.220376844793207 -5.048327719834068 other other other other text/xml other other geonode:trees_ad4fd8bef864d665041c2b4aad402a3c The distribution of trees in Urban West as digitized from high resolution drone imagery. vegetation natural features tree trees_ad4fd8bef864d665041c2b4aad402a3c trees urban ecology EPSG:32737 CRS:84 39.189105737380046 39.22652121849624 -6.202771313171629 -6.135205050047756 other other other other text/xml other other geonode:tungamalenga_500_lschar 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. Tungamalenga features tungamalenga_500_lschar EPSG:32736 CRS:84 35.06681459162393 35.12609854752434 -7.877423434632104 -7.80481377342392 other other other other text/xml other other other other other other text/xml other other geonode:tungamalenga_lulc 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. tungamalenga_lulc features Tungamalenga EPSG:32736 CRS:84 35.06677870555523 35.12609863915747 -7.8774415506864734 -7.804831711384936 text/xml other other other other other other geonode:tungamalenga_road 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. features Tungamalenga tungamalenga_road EPSG:32736 CRS:84 35.06934909419128 35.12138438637268 -7.871956345158696 -7.812317808996844 other other other other text/xml other other other other other text/xml other other other geonode:tungamalenga_servicepoints 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. features tungamalenga_servicepoints Tungamalenga EPSG:32736 CRS:84 35.06939745543702 35.1206965396733 -7.8715404527792705 -7.797496026061434 other other other other text/xml other other geonode:tungamalenga_waterways 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. features Tungamalenga tungamalenga_waterways EPSG:32736 CRS:84 35.07949092571134 35.120176685331835 -7.849110579461916 -7.796518161049702 other other other other text/xml other other text/xml other other other other other other geonode:unguja_island_orthophoto_infogrid 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/ features unguja_island_orthophoto_infogrid EPSG:32737 CRS:84 39.17811879198595 39.58537404051361 -6.502988405612319 -5.715695765796133 other other other other text/xml other other other other other other text/xml other other geonode:unguja_shehia_corrected_update 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 unguja unguja_shehia_corrected_update shehia features wards EPSG:21037 CRS:84 39.18132764938562 39.58045545081221 -6.4783795976715695 -5.72168395982856 other text/xml other other other other other other other other other text/xml other other geonode:urban_green_2022_boreholes 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. urban_green_2022_boreholes urban greening boreholes features EPSG:4326 CRS:84 39.16131042 39.25613219 -6.93095297 -6.755708404 other other other other text/xml other other geonode:urban_green_2022_natural_drainagegpkg_wal 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. urban_green_2022_natural_drainagegpkg_wal natural drainage urban greening features EPSG:4326 CRS:84 39.23892187220915 39.24227625131607 -6.840754603047223 -6.839748445611456 other other other other text/xml other other geonode:urban_greening_buildings_polygon 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. buildings urban greening urban_greening_buildings_polygon features EPSG:4326 CRS:84 39.16110729777671 39.3510236977032 -6.932778394468582 -6.752047594688185 other other other other text/xml other other other other other other text/xml other other geonode:urban_greening_highways 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. highways urban greening urban_greening_highways features EPSG:4326 CRS:84 39.1607725 39.351003247950324 -6.932762874405568 -6.7519266 other other other other text/xml other other other other other other text/xml other other geonode:ward_boundaries_3f7b0f55ee9ba5ff1b1d6823c209cd35 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. boundaries ward_boundaries_3f7b0f55ee9ba5ff1b1d6823c209cd35 features Ward EPSG:21036 CRS:84 32.86117714918455 33.08188458450372 -2.655109160194678 -2.3728551756585428 other other other other text/xml other other geonode:wards_boundaries 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. boundaries administrative features wards_boundaries EPSG:21037 CRS:84 38.89133370960319 39.16493567791367 -5.261868449802658 -4.961119657972797 other other other other text/xml other other geonode:water_bodies This shows the locations of waterbodies. features water_bodies EPSG:32737 CRS:84 39.215406780291964 39.22348964019443 -6.1813769821775315 -6.16366372715208 other other other other text/xml other other geonode:water_treatment 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. infrastructure water features water_treatment EPSG:21037 CRS:84 38.965888248222555 38.97138119484421 -5.061125593281355 -5.055211512579231 other other other other text/xml other other geonode:waterpipe_network 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. waterpipe_network water infrastructure features EPSG:21037 CRS:84 38.9609293018013 39.13004650222298 -5.151802107136359 -5.054665631634319 other other other other text/xml other other geonode:wsf2015_v2_38__8_output The World Settlement Footprint WSF 2015 version 2 (WSF2015 v2) is a 10m resolution binary mask outlining the extent of human settlements globally for the year 2015. Specifically, the WSF2015 v2 is a pilot product generated by combining multiple datasets, namely:• The WSF2015 v1 derived at 10m spatial resolution by means of 2014-2015 multitemporal Landsat-8 and Sentinel-1 imagery (of which ~217K and ~107K scenes have been processed, respectively); https://doi.org/10.1038/s41597-020-00580-5• The High Resolution Settlement Layer (HRSL) generated by the Connectivity Lab team at Facebook through the employment of 2016 DigitalGlobe VHR satellite imagery and publicly released at 30m spatial resolution for 214 countries; https://arxiv.org/pdf/1712.05839.pdf• The novel WSF2019 v1 derived at 10m spatial resolution by means of 2019 multitemporal Sentinel-1 and Sentinel-2 imagery (of which ~ 1.2M and ~1.8M scenes have been processed, respectively); https://doi.org/10.1553/giscience2021_01_s33The WSF2015 v1 demonstrated to be highly accurate, outperforming all similar existing global layers; however, the use of Landsat imagery prevented a proper detection of very small structures, mostly due to their reduced scale. Based on an extensive qualitative assessment, wherever available the HRSL layer shows instead a systematic underestimation of larger settlements, whereas it proves particularly effective in identifying smaller clusters of buildings down to single houses, thanks to the employment of 2016 VHR imagery. The WSF2015v v2 has been then generated by: i) merging the WSF2015 v1 and HRSL (after resampling to 10m resolution and disregarding the population density information attached); and ii) masking the outcome by means of the WSF2019 product, which exhibits even higher detail and accuracy, also thanks to the use of Sentinel-2 data and the proper employment of state-of-the-art ancillary datasets (which allowed, for instance, to effectively mask out all roads globally from motorways to residential). land cover global Landsat-8 wsf2015_v2_38__8_output inspireidentifiziert land GeoTIFF settlement extent Sentinel-1 urbanization WCS opendata EPSG:4326 CRS:84 37.989933028471384 40.010064439399365 -8.010007893908536 -5.989966314508969 text/xml other other other other other other geonode:wsf2019_v1_38__8_output The World Settlement Footprint (WSF) 2019 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2019 multitemporal Sentinel-1 (S1) and Sentinel-2 (S2) imagery. Based on the hypothesis that settlements generally show a more stable behavior with respect to most land-cover classes, temporal statistics are calculated for both S1- and S2-based indices. In particular, a comprehensive analysis has been performed by exploiting a number of reference building outlines to identify the most suitable set of temporal features (ultimately including 6 from S1 and 25 from S2). Training points for the settlement and non-settlement class are then generated by thresholding specific features, which varies depending on the 30 climate types of the well-established Köppen Geiger scheme. Next, binary classification based on Random Forest is applied and, finally, a dedicated post-processing is performed where ancillary datasets are employed to further reduce omission and commission errors. Here, the whole classification process has been entirely carried out within the Google Earth Engine platform. To assess the high accuracy and reliability of the WSF2019, two independent crowd-sourcing-based validation exercises have been carried out with the support of Google and Mapswipe, respectively, where overall 1M reference labels have been collected based photointerpretation of very high-resolution optical imagery. land cover global Landsat-8 wsf2019_v1_38__8_output inspireidentifiziert land GeoTIFF Sentinel-1 urbanization WCS opendata EPSG:4326 CRS:84 37.989933028471384 40.010064439399365 -8.010007893908536 -5.989966314508969 other other other other text/xml other other geonode:wsf_building_areas This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents the overall building area in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building area means the sum of built floor area in square meters in one cell. In other words, the area of each floor of each building are calculated and added up together to reach the building area values. Multi-storey buildings has much more built floor area than lower houses, and therefore usually the city centers with high buildings has higher building area than the suburbs. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. building area exposure wsf_building_areas GeoTIFF WSF-3D WCS EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other other other other other text/xml other other geonode:wsf_building_areas_output This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents the overall building area in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building area means the sum of built floor area in square meters in one cell. In other words, the area of each floor of each building are calculated and added up together to reach the building area values. Multi-storey buildings has much more built floor area than lower houses, and therefore usually the city centers with high buildings has higher building area than the suburbs. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. building area exposure wsf_building_areas_output GeoTIFF WSF-3D WCS EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other geonode:wsf_building_height_ This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents building heights in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building volume means how much there is building material in cubic meters in one raster cell. In other words, the height x width x depth of all buildings in one cell are calculated together to achieve the building volume value in cubic meters. Very high volumes are due to multi-storey buildigns, and therefore usually the city centers with high buildings has higher building volume than suburban areas. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. building height exposure wsf_building_height_ GeoTIFF WSF-3D WCS EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other other other other other text/xml other other geonode:wsf_building_height_output This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents building heights in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building volume means how much there is building material in cubic meters in one raster cell. In other words, the height x width x depth of all buildings in one cell are calculated together to achieve the building volume value in cubic meters. Very high volumes are due to multi-storey buildigns, and therefore usually the city centers with high buildings has higher building volume than suburban areas. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. building height exposure GeoTIFF WSF-3D wsf_building_height_output WCS EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other geonode:wsf_building_volume This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents building volumes in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building volume means how much there is building material in cubic meters in one raster cell. In other words, the height x width x depth of all buildings in one cell are calculated together to achieve the building volume value in cubic meters. Very high volumes are due to multi-storey buildigns, and therefore usually the city centers with high buildings has higher building volume than suburban areas. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. exposure GeoTIFF building volume WSF-3D WCS wsf_building_volume EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other other other other other text/xml other other geonode:wsf_building_volume_output This layer has been derived from the World Settlemet Footprint 3D 2019 dataset. It represents building volumes in the Dar es Salaam region, with a 90x90 meter spatial resolution. Building volume means how much there is building material in cubic meters in one raster cell. In other words, the height x width x depth of all buildings in one cell are calculated together to achieve the building volume value in cubic meters. Very high volumes are due to multi-storey buildigns, and therefore usually the city centers with high buildings has higher building volume than suburban areas. *** This dataset was produced by The German Aerospace Center (DLR) in collaboration with MindEarth, and validated by university students from four Tanzanian universities (ARU, SUA, SUZA, UDSM partners of the Resilience Academy) by using crowd-labeling methods. exposure wsf_building_volume_output GeoTIFF building volume WSF-3D WCS EPSG:4326 CRS:84 29.341277811111127 40.436277811111125 -11.740055599999991 -0.9973889333333261 other other other other text/xml other other geonode:zanzibar_government_forests This dataset represents government owned forests in Pemba and Unguja islands of Zanzibar. Data was created during the ZEIMS (Zanzibar Environmental Information System) project. features forests zanzibar_government_forests environment ZanSea EPSG:32737 CRS:84 39.22043368448776 39.8762413808651 -6.282451054641167 -4.88709884314647 text/xml other other other other other other geonode:zoo 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. Planning zoo Urban features EPSG:21037 CRS:84 38.96035640553694 38.99198048934253 -5.09960617887946 -5.082389550665679 other other other other text/xml other other