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"title": "Indonesia", "description": "UrbanShift for Indonesia", "keyword": [ "" ], "issued": "2022-04-20T17:20:52.000Z", "modified": "2022-04-21T11:51:22.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Logan.Byers_wri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/pages/worldresources::indonesia" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=098e6f53ea9d4393b5ba549b08ab0065", "landingPage": "https://datahub.shiftcities.org/pages/worldresources::india", "title": "India", "description": "UrbanShift for India", "keyword": [ "" ], "issued": "2022-04-20T17:16:13.000Z", "modified": "2022-04-21T11:50:43.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Logan.Byers_wri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/pages/worldresources::india" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=c49b27a0f21946e6807e71ed107d3aae", "landingPage": "https://datahub.shiftcities.org/pages/worldresources::china", "title": "China", "description": "UrbanShift for China", "keyword": [ "" ], "issued": "2022-04-20T17:18:47.000Z", "modified": "2022-04-21T11:49:15.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Logan.Byers_wri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/pages/worldresources::china" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=84263d6ab59442e9ba11436298f9dab9", "landingPage": "https://datahub.shiftcities.org/pages/worldresources::brazil", "title": "Brazil", "description": "UrbanShift for Brazil", "keyword": [ "" ], "issued": "2022-04-20T16:58:03.000Z", "modified": "2022-04-21T11:48:30.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Logan.Byers_wri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/pages/worldresources::brazil" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7ab524da75104e4291c130c20bb33e7a", "landingPage": "https://datahub.shiftcities.org/pages/worldresources::argentina", "title": "Argentina", "description": "UrbanShift for Argentina", "keyword": [ "" ], "issued": "2022-04-20T17:24:05.000Z", "modified": "2022-04-21T11:47:54.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Logan.Byers_wri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/pages/worldresources::argentina" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3995080710aa45439748f83c333e637a&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::impervious-surfaces-in-cri-san-jose-2018", "title": "Impervious surfaces in CRI-San Jose 2018", "description": "This layer presents land classified as impervious to water infiltration in year 2018. It is derived from a dataset that contains annual change information of global impervious surface area from 1985 to 2018 at a 30m resolution. Change from pervious to impervious was determined using a combined approach of supervised classification and temporal consistency checking. Impervious pixels are defined as above 50% impervious. The dataset is temporally consistent, following the conversion from pervious (e.g., non-urban) to impervious (e.g., urban) monotonically. 

Click here to download TIF version of layer
", "keyword": [ "UrbanShift", "CRI-San_Jose", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2018", "Biodiversity", "Built-up", "Format:Raster", "Land_Cover" ], "issued": "2022-04-16T02:58:18.000Z", "modified": "2022-04-20T19:15:33.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4700,9.5508,-83.6458,10.4142", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::impervious-surfaces-in-cri-san-jose-2018" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_GAIA_impervious_surfaces2018/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=901ee2ae4b6c4f098c738f7102dc60a0&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::habitat-change-for-cri-san-jose-between-2000-and-2020", "title": "Habitat change for CRI-San Jose between 2000 and 2020", "description": "This dataset presents change in land use between 2000 and 2020 as aggregated into changes between habitat and non-habitat classes. Land cover classes for each year are derived from GLAD Global Land Cover and Land Use Change. Aquatic or non-cropland vegetated classes are aggregated as habitat classes. Urban, cropland and bare classes are aggregated as nonhabitat. The resulting map presents changes in land classification from nonhabitat to habitat (habitat gain) and from habitat to nonhabitat (habitat loss). 

Click here to download TIF version of layer
", "keyword": [ "UrbanShift", "CRI-San_Jose", "Land_Use", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2000", "Time:2020", "Biodiversity", "Land_Restoration", "Habitat", "Format:Raster", "Land_Cover" ], "issued": "2022-04-16T02:56:26.000Z", "modified": "2022-04-20T19:15:11.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4700,9.5508,-83.6458,10.4142", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::habitat-change-for-cri-san-jose-between-2000-and-2020" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_GLAD_habitat_changes_2000_2020/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6b885580b99141ec893cd59470be5bb2&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::esa-world-cover-land-cover-extract-for-cri-san-jose", "title": "ESA World cover land cover extract for CRI-San Jose", "description": "The European Space Agency (ESA) WorldCover 10 m 2020 product provides a global land cover map for 2020 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes, aligned with UN-FAO’s Land Cover Classification System, and has been generated in the framework of the ESA WorldCover project. The World Cover product comes with 11 land cover classes: Tree cover, Shrubland, Grassland, Cropland, Built-up, Bare / sparse vegetation, Snow and ice, Open water, Herbaceous wetland, Mangroves, Moss and lichen.

\n\nClick here to download TIF version of layer", "keyword": [ "UrbanShift", "CRI-San_Jose", "Biodiversity", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2020", "Format:Raster", "Land_Cover" ], "issued": "2022-04-16T02:54:41.000Z", "modified": "2022-04-20T19:11:56.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4689,9.5511,-83.6464,10.4137", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::esa-world-cover-land-cover-extract-for-cri-san-jose" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_ESA_landcover2020/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=525bcd8145674f4c90410863ad9df337&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::land-cover-for-cri-san-jose-2020-glad-global-land-cover-and-land-use-change", "title": "Land cover for CRI-San Jose 2020 (GLAD Global Land Cover and Land Use Change)", "description": "The Global Land Analysis & Discovery (GLAD) lab at University of Maryland has produced Global Land Cover and Land Use Change, which provides a 30 meter resolution map of global land cover change between 2000 and 2020 generated from Landsat Analysis Ready Data. The map derived from this dataset for this study region and year distinguishes ten land cover classes: Bare Ground, Short Vegetation, Forest, Tall Forest (20m+), Wetland - Short Vegetation, Wetland - Forest, Water, Snow/Ice, Cropland, and Built-Up Area.

Click here to download TIF version of layer
", "keyword": [ "UrbanShift", "CRI-San_Jose", "Land_Cover", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2020", "Biodiversity", "Land_Restoration", "Format:Raster" ], "issued": "2022-04-16T03:00:21.000Z", "modified": "2022-04-20T19:11:23.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4700,9.5508,-83.6458,10.4142", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::land-cover-for-cri-san-jose-2020-glad-global-land-cover-and-land-use-change" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_GLADlandcover2020/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f8c6654c1a0b4473b4286084d2b114ae&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::land-cover-for-cri-san-jose-2000-glad-global-land-cover-and-land-use-change", "title": "Land cover for CRI-San Jose 2000 (GLAD Global Land Cover and Land Use Change)", "description": "The Global Land Analysis & Discovery (GLAD) lab at University of Maryland has produced Global Land Cover and Land Use Change, which provides a 30 meter resolution map of global land cover change between 2000 and 2020 generated from Landsat Analysis Ready Data. The map derived from this dataset for this study region and year distinguishes ten land cover classes: Bare Ground, Short Vegetation, Forest, Tall Forest (20m+), Wetland - Short Vegetation, Wetland - Forest, Water, Snow/Ice, Cropland, and Built-Up Area.

Click here to download TIF version of layer
", "keyword": [ "UrbanShift", "CRI-San_Jose", "Land_Cover", "Land_Use", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2000", "Biodiversity", "Land_Restoration", "Format:Raster" ], "issued": "2022-04-16T02:53:51.000Z", "modified": "2022-04-20T19:10:54.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4700,9.5508,-83.6458,10.4142", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::land-cover-for-cri-san-jose-2000-glad-global-land-cover-and-land-use-change" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_GLADlandcover2000/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9d6a26af01514613bc7d4d4405081137&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::land-surface-temperature-for-cri-san-jose-march-may-2021", "title": "Land surface temperature for CRI-San Jose March-May 2021", "description": "A map of mean land surface temperature is derived for this study region and period using algorithms from Ermida et al. (https://doi.org/10.3390/rs12091471) applied through Google Earth Engine to imagery collected by the Landsat series of remote sensing satellites. The resulting map provides estimates of mean land surface temperature in degrees Celsius for March through May 2021, in the hottest months in the San Jose region that year. Estimates are unavailable for some areas with persistent cloud cover. 

Click here to download TIF version of layer
", "keyword": [ "CRI-San_Jose", "Land_Cover", "Land_Use", "Geography:America", "Geography:America:Costa_Rica", "Geography:America:Costa_Rica:San_Jose", "Time:2021", "Time:2021-03MAR", "Time:2021-04APR", "Time:2021-05MAY", "Biodiversity", "Land_Restoration", "Weather", "Heat", "Climate", "Format:Raster" ], "issued": "2022-04-14T00:41:04.000Z", "modified": "2022-04-20T19:08:20.000Z", "publisher": { "name": "World Resources Institute" }, "contactPoint": { "@type": "vcard:Contact", "fn": "eric.mackres_worldresources", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-84.4690,9.5509,-83.6463,10.4138", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://datahub.shiftcities.org/maps/worldresources::land-surface-temperature-for-cri-san-jose-march-may-2021" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://tiles.arcgis.com/tiles/hBEMHCkbQdfV906F/arcgis/rest/services/CRI_San_Jose_LSTmean2021_0305/MapServer/0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=99b70124aaab4a9eadddc1751e47faae&sublayer=0", "landingPage": "https://datahub.shiftcities.org/maps/worldresources::gridded-population-estimates-for-cri-san-jose-2020", "title": "Gridded population estimates for CRI-San Jose 2020", "description": "This dataset depicts estimated number of people residing in each grid cell in 2020. Full details on the methods and datasets used in constructing the data, along with open access publications, are provided on the WorldPop website. In brief, recent census-based population counts matched to their associated administrative units are disaggregated to ~100x100m grid cells through machine learning approaches that exploit the relationships between population densities and a range of geospatial covariate layers. The mapping approach is Random Forest-based dasymetric redistribution. 

Click here to download TIF version of layer
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