HydroBASINS is covered by the same License Agreement as the HydroSHEDS database, which is available at hydrosheds.org. For all regulations regarding license grants, copyright, redistribution restrictions, required attributions, disclaimer of warranty, indemnification, liability, waiver of damages, and a precise definition of licensed materials, please refer to the License Agreement. By downloading and using the data the user agrees to the terms and conditions of the License Agreement.
This layer may not be downloaded, altered or edited without the permission of Anchor Environmental Consultants, Environmental Incentives or USAID.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/datasets/rcmrd::hydrosheds-level-6" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services6.arcgis.com/zOnyumh63cMmLBBH/arcgis/rest/services/HydroSheds_lev6/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://rcmrd.africageoportal.com/api/download/v1/items/a91b33c190064f388c0edaa29b318368/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://rcmrd.africageoportal.com/api/download/v1/items/a91b33c190064f388c0edaa29b318368/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://rcmrd.africageoportal.com/api/download/v1/items/a91b33c190064f388c0edaa29b318368/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://rcmrd.africageoportal.com/api/download/v1/items/a91b33c190064f388c0edaa29b318368/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7eafbb81ca114901a6315b2fa7fccad2&sublayer=0", "landingPage": "https://rcmrd.africageoportal.com/datasets/rcmrd::gorilla-habitat-suitability", "title": "Gorilla Habitat Suitability", "description": "Blue wildebeest habitat suitability under near-historic climate and under future climate in ca. 2050 based on three different CMIP5 climate models. Data sourced from Conservation International (2018).The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Grouped habitat map (22 classes) of the original 72 habitat types across the study region in East Africa for the project 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Following the data collation and regional overview, a detailed analysis was undertaken at a regional (East Africa) scale of spatial data on vegetation types, ecoregions, land cover, and biomass in conjunction with relevant ecological literature. Estimating the supply of ecosystem services across the landscape requires a detailed representation of land cover and vegetation characteristics, as these have a strong influence over the spatial distribution and value of services provided. Our chosen ecosystem delineation method involved a combination of the land cover, vegetation type, and land condition datasets. We felt that combining these datasets to produce a single map of habitat types would produce the most accurate possible representation of habitats across East Africa for the purposes of ecosystem service valuation. We also used the IUCN’s Global Ecosystem typology to aid with the grouping of the habitat types we identified.
The following datasets were used to produce our habitat map:
• Copernicus 100-meter land cover data for 2018 (Copernicus Global Land Operations);
• Potential natural vegetation map for East and Southern Africa (van Breugel et al., 2015) (WWF Ecoregions map used instead for South Sudan); and
• Change in the normalized difference vegetation index (NDVI) between 2001 and 2018 (Trends.Earth).
There are 16 forest habitat types, 14 woodland habitat types, 12 grassland/wooded grassland habitat types, 19 bushland/shrubland habitat types, 5 aquatic habitat types, 4 desert/bare habitat types, and 2 anthropogenic types (cultivation built-up). The number of habitat types within each study area ranged from 19 in the Rweru-Mugesera-Akagera Wetlands to 51 habitat types in the Great East African Plains.
Blue wildebeest habitat suitability under near-historic climate and under future climate in ca. 2050 based on three different CMIP5 climate models. Data sourced from Conservation International (2018).
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Blue wildebeest habitat suitability under near-historic climate and under future climate in ca. 2050 based on three different CMIP5 climate models. Data sourced from Conservation International (2018).
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Gridded Population at ~1 ha resolution for the year 2018. Data derived from worldpop.org.
The Eastern\nand Africa Land Cover Viewer is a web mapping application designed for the visualization\nof the yearly land cover maps from 2000 to 2017 for the Eastern and Southern\nAfrican nations namely: Zambia, Malawi, Tanzania, Rwanda, Kenya, Uganda, and\nEthiopia. The map legend corresponds to the Intergovernmental Panel on Climate\nChange (IPCC) land categories for reporting of greenhouse gas emissions: Forest\nland, Grassland, Cropland, Wetlands, Settlement, and Other land. To facilitate\ncreation of the dataset, a series of workshops were conducted with local\nrepresentatives in each country in 2017, 2018, and 2019. This dataset was\ncreated using the Continuous Change Detection and Classification (CCDC) algorithm\non the Google Earth Engine. CCDC uses time series analysis of Landsat data to\nmonitor for land cover or condition change at 30-meter spatial resolution.
", "keyword": [ "landcover", "landuse", "africa", "servir", "admin2", "rcmrd" ], "issued": "2020-09-24T09:32:01.000Z", "modified": "2022-12-09T16:23:21.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "PKabatha", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/apps/rcmrd::eastern-and-southern-africa-land-cover-viewer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://rcmrd.maps.arcgis.com/apps/webappviewer/index.html?id=c954194840d74c48a760485fe00ffb1e" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=fe200cff94624a938b042d68beeaa13a", "landingPage": "https://rcmrd.africageoportal.com/datasets/esri::european-space-agency-climate-change-initiative-land-cover-2018", "title": "European Space Agency Climate Change Initiative - Land Cover 2018", "description": "Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.
This layer displays global land cover in 10 classes for the year 2018 produced by the European Space Agency Climate Change Initiative (ESA CCI). The 36 classes of the traditional ESA CCI land cover has been simplified to match the Esri 2050 land cover prediction layers.
This layer may be displayed in a map to show generalized land cover classes for the world in the year 2018.
This data layer represents country boundaries that are covered by the Nile basin drainage, derived from the GADM global datasets.
The map was prepared from the image processing of ALOS AVNIR-2 ( 189 SCENES of Date 20/3/2009 - 15/2/2011 and DMC (9 SCENES of 6/9/2010 - 13/4/2011) with field validation.
Projection: Arc 1960_Universal Transverse Mercator_Zone 37S
This Maps Viewer shows all the maps that are in the Elgeyo Marakwet County Hazard Atlas.
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"https://www.arcgis.com/home/item.html?id=45aef78a33b243529be22cac4a4d57b5", "landingPage": "https://rcmrd.africageoportal.com/apps/rcmrd::wajir-county-hazard-atlas-maps-viewer", "title": "Wajir County Hazard Atlas (Maps Viewer)", "description": "This Maps Viewer shows all the maps that are in the Wajir County Hazard Atlas", "keyword": [ "Wajir", "County", "Hazard", "Atlas", "Kenya", "Maps Viewer", "UNDP", "NDMA", "RCMRD" ], "issued": "2022-06-08T06:12:55.000Z", "modified": "2022-06-08T06:15:06.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "fadamullah_rcmrd", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/apps/rcmrd::wajir-county-hazard-atlas-maps-viewer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/wajir/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f7c2b6d89d094eaabad648a393ec1ddc", "landingPage": "https://rcmrd.africageoportal.com/apps/rcmrd::west-pokot-county-hazard-atlas-maps-viewer", "title": "West Pokot County Hazard Atlas (Maps Viewer)", "description": "This Maps Viewer shows all the maps that are in the West Pokot County Hazard Atlas", "keyword": [ "West Pokot", "County", "Hazard", "Atlas", "Kenya", "Maps Viewer" ], "issued": "2022-06-07T15:15:06.000Z", "modified": "2022-06-07T15:48:34.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "fadamullah_rcmrd", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/apps/rcmrd::west-pokot-county-hazard-atlas-maps-viewer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/west_pokot/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=c4cee9f0ced14d60988f651050fcda6f", "landingPage": "https://rcmrd.africageoportal.com/documents/rcmrd::wajir-county-hazard-atlas-pdf", "title": "Wajir County Hazard Atlas (PDF)", "description": "This Atlas is in PDF format showing the Wajir County Hazards", "keyword": [ "Wajir", "County", "Hazard", "Atlas", "PDF", "Kenya", "UNDP", "NDMA", "RCMRD" ], "issued": "2022-06-07T13:47:06.000Z", "modified": "2022-06-07T13:49:56.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "fadamullah_rcmrd", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/documents/rcmrd::wajir-county-hazard-atlas-pdf" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/wajir/atlaspdf/wajir_county_atlas.pdf" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=df30009bc1874917906bb4b3c0cb09ad", "landingPage": "https://rcmrd.africageoportal.com/documents/rcmrd::elgeyo-marakwet-county-hazard-atlas-pdf", "title": "Elgeyo Marakwet County Hazard Atlas (PDF)", "description": "This Atlas is in PDF format showing the Elgeyo Marakwet County Hazards
", "keyword": [ "Elgeyo Marakwet", "County", "Hazard", "Atlas", "PDF", "Kenya", "UNDP", "NDMA", "RCMRD" ], "issued": "2022-06-07T07:13:14.000Z", "modified": "2022-06-07T13:42:25.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "fadamullah_rcmrd", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/documents/rcmrd::elgeyo-marakwet-county-hazard-atlas-pdf" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/elgeyo_marakwet/atlaspdf/elgeyo_marakwet_atlas.pdf" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=deb45d37c4eb4b91904e25b8e81be34d", "landingPage": "https://rcmrd.africageoportal.com/documents/rcmrd::isiolo-county-hazard-atlas-pdf", "title": "Isiolo County Hazard Atlas (PDF)", "description": "{{description}}", "keyword": [ "Atlas", "Isiolo", "isiolo hazard atlas" ], "issued": "2022-03-04T07:35:36.000Z", "modified": "2022-06-07T06:34:30.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "rcmrd_online", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/documents/rcmrd::isiolo-county-hazard-atlas-pdf" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/isiolo/atlaspdf/isiolo_county_atlas.pdf" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a50972a0b8a04d59ab3fa19e2fd771ec", "landingPage": "https://rcmrd.africageoportal.com/apps/rcmrd::isiolo-county-hazard-atlas-maps-viewer", "title": "Isiolo County Hazard Atlas (Maps Viewer)", "description": "This Maps Viewer shows all the maps that are in the Isiolo County Hazard Atlas", "keyword": [ "Isiolo", "County", "Hazard", "Maps", "Viewer" ], "issued": "2022-03-04T08:51:40.000Z", "modified": "2022-06-07T06:34:07.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "rcmrd_online", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "", "license": "https://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/apps/rcmrd::isiolo-county-hazard-atlas-maps-viewer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://apps.rcmrd.org/atlases/isiolo/index.html" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=4032344be80f477e82ff89c3fd3cfe42", "landingPage": "https://rcmrd.africageoportal.com/maps/rcmrd::south-sudan-datasets", "title": "South Sudan Datasets", "description": "{{description}}", "keyword": [ "gmes", "gmes_ogrvd", "gmes_southsudan_ogrvd", "rcmrd" ], "issued": "2022-04-26T04:53:29.000Z", "modified": "2022-04-26T04:55:06.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "rcmrd_online", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "18.1046,1.1069,41.0880,13.8248", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/maps/rcmrd::south-sudan-datasets" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9d1afb393279405db0fc8b4943d562d6", "landingPage": "https://rcmrd.africageoportal.com/maps/rcmrd::africaterrestialecosystems", "title": "AfricaTerrestialEcosystems", "description": "{{description}}", "keyword": [ "africa", "ecosystems", "2013" ], "issued": "2018-03-05T18:19:12.000Z", "modified": "2021-11-23T13:14:12.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "PKabatha", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "-29.0290,-29.5934,62.9046,15.1349", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/maps/rcmrd::africaterrestialecosystems" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=2acd5c3d260a4e8a898d63ee3a566b9f", "landingPage": "https://rcmrd.africageoportal.com/apps/rcmrd::ethiopia-gmes-web-mapping-application", "title": "Ethiopia GMES Web Mapping Application", "description": "This product has been\ndeveloped using the (Revised Universal Soil Loss Equation) RUSLE. Among the key\nparameters used include: soil
\n\nerosivity, slope,\nrainfall intensity, population and land cover.
\n\n\n\n
Online distribution\ninformation:
\n\nFile Data Format: Zipped\nGeoTIFF
\n\nOnline location: Click to Download
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forestry (LULUCF) sector.
The land surface forms were identified using the method developed by the Missouri Resource Assessment Partnership (MoRAP). The MoRAP method is an automated land surface form classification based on Hammond's (1964a, 1964b) classification. MoRAP made modifications to Hammond's classification, which allowed finer-resolution elevation data to be used as input data and analyses to be made using 1 km2 moving window (True, 2002; True et al., 2000). While Hammond's methodology was based on three variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief (True, 2002). Slope is classified as gently sloping or not gently sloping using a threshold value of 8%. Local relief, the difference between the maximum and minimum elevation in a 1km2 neighborhood for analysis, is classified into five classes (0-15m, 16-30m, 31-90m, 91-150m, and >150m). Slope classes and relief classes were subsequently combined to produce eight land surface form classes (flat plains, smooth plains, irregular plains, escarpments, low hills, hills, breaks/foothills, and low mountains). In the implementation for the contiguous United States, Sayre et al. (2009) further refined the MoRAP methodology to identify a new land surface form class, "high mountains/deep canyons", by using an additional local relief class (>400 m). This method was implemented for Africa using a void-filled 90m SRTM elevation dataset which was created from the 30m SRTM elevation data provided by the National Geospatial-Intelligence Agency. In the preliminary output, which had nine land surface form classes (flat plains, smooth plains, irregular plains, escarpments, low hills, hills, breaks/foothills, and low mountains, and high mountains/deep canyons), artifacts were identified over flat desert areas affecting the classification between the two lowest relief classes, "flat plains" and "smooth plains." Since this problem was especially pronounced in areas where the input SRTM elevation data originally had data-voids, the problem could have been caused by anomalies or artifacts in the input data, which resulted from the void-filling processes. Instead of further investigating causes of the problem, the two land surface form classes were combined. In addition, the "low hills" class which had a very low occurrence was combined with the "hills" class. As a result, seven land surface form classes were identified in the final dataset (smooth plains, irregular plains, escarpments, hills, breaks/foothills, low mountains, and high mountains/deep canyons). References: Hammond, E.H., 1964a. Analysis of Properties in Land Form Geography - An Application to Broad-Scale Land Form Mapping. Annals of the Association of American Geographers, v. 54, no. 1, p. 11-19. Hammond, E.H. 1964b. Classes of land surface form in the forty-eight states, U.S.A. Annals of the Association of American Geographers. 54(1): map supplement no. 4, 1: 5,000,000. Sayre, R., P. Comer, H. Warner, and J. Cress. 2009. A new map of standardized terrestrial ecosystems of the conterminous United States: U. S. Geological Survey professional Paper 1768, 17 p. True, D. 2002. Landforms of the Lower Mid-West. Missouri Resource Assessment Partnership. MoRAP Map Series MS-2003-001, scale 1:1,500,000. <http://www.cerc.usgs.gov/morap/Assets/maps/Landforms_of_the_Lower_Mid-West_MS-2002-01.pdf>. True, D., T. Gordon, and D. Diamond. 2000. How the size of a sliding window impacts the generation of landforms. Missouri Resources Assessment Partnership. <http://www.cerc.cr.usgs.gov/morap/projects/landform_model/landforms2001_files/frame.htm>.
", "keyword": [ "servir_esa", "Climate", "Temperature", "Precipitation", "Vegetation", "Ecosytems", "Environment", "thermotypes", "ombrotypes", "bioclimates", "USGS", "Biodiversity", "Africa", "lulc-serviresa" ], "issued": "2017-06-16T07:41:45.000Z", "modified": "2023-08-23T13:25:06.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "PKabatha", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "-25.3615,-46.9828,63.5027,37.5422", "license": "http://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/datasets/rcmrd::africa-land-surface-forms" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://maps.rcmrd.org/arcgis/rest/services/Africa/Africa_Land_Surface/ImageServer" }, { "@type": "dcat:Distribution", "title": null, "format": null, "accessURL": "http://maps.rcmrd.org/arcgis/rest/services/AfricaContinent/Africa_Land_Surface/ImageServer", "description": null }, { "@type": "dcat:Distribution", "title": "Zipped Download", "format": null, "accessURL": "https://s3.amazonaws.com/rcmrd-open-data/downloadable_files/Africa_LandSurface_Forms.zip", "description": null } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=beccb3d4300c4c01974ff3f8befe993f", "landingPage": "https://rcmrd.africageoportal.com/datasets/rcmrd::africa-isobioclimates", "title": "Africa IsoBioclimates", "description": "Climate - in terms of temperature, precipitation and continentality - \nis a primary determinant in the distribution of vegetation. \nSalvador Rivas-Martinez and Salvador Rivas-Saenz (2004) developed a global bioclimatic classification system \nthat quantifies key bioclimatic indices reflective of vegetation distributions. These indices can be used to \nmodel thermotypes (i.e. hot-cold gradients), ombrotypes (i.e. wet-dry gradients), and bioclimates (continentality gradients). \nTheir model was translated into GIS spatial algorithms during modeling of the US ES bioclimate data (Warner et. al. 2008). \nThese spatial models were used (with minor adaptations) with Worldclim climatological data (Hijmans et. al. 2005) \nto model/map bioclimates, ombrotypes and thermotypes. These three maps were then combined into an isobioclimate map \nwith a total of 428 composite classes (e.g. Composite isobioclimate gridcode 2036 equals Tropical Pluvialseasonal (2000), \nLower Thermotropical (30), Subhumid (6)).", "keyword": [ "africa", "Climate", "Temperature", "Precipitation", "Vegetation", "Ecosytems", "Environment", "thermotypes", "ombrotypes", "bioclimates", "USGS", "Biodiversity", "serviresa", "wc-serviresa" ], "issued": "2017-06-09T09:57:29.000Z", "modified": "2023-08-18T09:56:22.000Z", "publisher": { "name": "Regional Centre for Mapping of Resource for Development" }, "contactPoint": { "@type": "vcard:Contact", "fn": "PKabatha", "hasEmail": "mailto:rcmrd@rcmrd.org" }, "accessLevel": "public", "spatial": "-25.3615,-46.9828,63.5019,37.5422", "license": "http://opendatacommons.org/licenses/odbl/summary", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://rcmrd.africageoportal.com/datasets/rcmrd::africa-isobioclimates" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://maps.rcmrd.org/arcgis/rest/services/Africa/Africa_Isobioclimates/ImageServer" }, { "@type": "dcat:Distribution", "title": null, "format": null, "accessURL": "https://maps.rcmrd.org/arcgis/rest/services/AfricaContinent/Africa_IsoBioclimates/ImageServer", "description": null }, { "@type": "dcat:Distribution", "title": "Zipped Download", "format": null, "accessURL": "https://s3.amazonaws.com/rcmrd-open-data/downloadable_files/Africa_IsoBioClimates.zip", "description": null } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3d2eb7247f2846008fb63c5bfb4ee456&sublayer=0", "landingPage": "https://rcmrd.africageoportal.com/maps/rcmrd::kenya-land-degradation-monitoring-and-assessment-2019-season-1", "title": "Kenya Land Degradation Monitoring and Assessment 2019 (Season-1)", "description": "The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Total annual baseflow contribution (Megalitres/y) per sub-basin in each wildlife landscape.
Values are sumarised at sub-basin level using HydroBASINS. All HydroBASINS layers were derived from World Wildlife Fund’s HydroSHEDS data based on a grid resolution of 15 arc-seconds (approximately 500 m at the equator). Watersheds were delineated in a consistent manner at different scales, and a hierarchical sub-basin breakdown was created following the topological concept of the Pfafstetter coding system. The resulting polygon layers are termed HydroBASINS and represent a subset of the HydroSHEDS database. This shapefile contains (sub-)basin polygons for Africa at Pfafstetter level 6.
HydroBASINS is covered by the same License Agreement as the HydroSHEDS database, which is available at hydrosheds.org. For all regulations regarding license grants, copyright, redistribution restrictions, required attributions, disclaimer of warranty, indemnification, liability, waiver of damages, and a precise definition of licensed materials, please refer to the License Agreement. By downloading and using the data the user agrees to the terms and conditions of the License Agreement.
This layer may not be downloaded, altered or edited without the permission of Anchor Environmental Consultants, Environmental Incentives or USAID.
The layer was derived as part of the work conducted for the report: 'ECONOMIC VALUE OF EAST AFRICA’S TRANSBOUNDARY WILDLIFE LANDSCAPES: A Preliminary Natural Capital Assessment of Four Selected Landscapes and Assessment of the Current Trajectory'.
Total annual sediment retained (Megatonnes/y) per sub-basin in each wildlife landscape.
Values are sumarised at sub-basin level using HydroBASINS. All HydroBASINS layers were derived from World Wildlife Fund’s HydroSHEDS data based on a grid resolution of 15 arc-seconds (approximately 500 m at the equator). Watersheds were delineated in a consistent manner at different scales, and a hierarchical sub-basin breakdown was created following the topological concept of the Pfafstetter coding system. The resulting polygon layers are termed HydroBASINS and represent a subset of the HydroSHEDS database. This shapefile contains (sub-)basin polygons for Africa at Pfafstetter level 6.
HydroBASINS is covered by the same License Agreement as the HydroSHEDS database, which is available at hydrosheds.org. For all regulations regarding license grants, copyright, redistribution restrictions, required attributions, disclaimer of warranty, indemnification, liability, waiver of damages, and a precise definition of licensed materials, please refer to the License Agreement. By downloading and using the data the user agrees to the terms and conditions of the License Agreement.
This layer may not be downloaded, altered or edited without the permission of Anchor Environmental Consultants, Environmental Incentives or USAID.