This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 29 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 36 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software.

https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This service shows the datasets listed below. All datasets are in the ITM coordnate system. This data is subject to change and will be updated from time to time. Datasets included in this zip are - Business Area Units -Forest boundary - Property boundary - Compartment boundary - Forest Inventory . Please refer to terms of use for this dataset before using. These are available below or on the Coillte Public Viewer. The link to this is also included on this page below. Use of data All data on this viewer is available to download and subject to the terms of use – by downloading the data you are agreeing to the terms of use. Data is in ITM format. You agree not to copy, publish or use the data on another website or in any manner likely to confuse members of the public or amount to misrepresentation as to your identity or relationship with Coillte. You agree not to access the data contained therein in any way which is unlawful, illegal, fraudulent or harmful or in connection with any for any unlawful, illegal, fraudulent or harmful activity, including data privacy breaches. The dataset is made available free of charge. We do not guarantee that this dataset, or any content in our Arc GIS online platform, will always be available or be uninterrupted. Coillte may suspend or withdraw or restrict the availability of all or part of the Viewer for business or operational reasons. The content on the Coillte ArcGIS platform is for general information only. Reasonable care has been exercised in the compilation of the information available through the ArcGIS online platform. There is no representation or warranty made as to the accuracy, completeness or currency of such information. The use of any such information, which may be altered or updated at any time without notice, is at the sole risk of the user. Coillte cannot accept responsibility for any errors or omissions or any consequential loss as a result of the same. Before relying on the information on this site, users should carefully evaluate its accuracy, currency, completeness and relevance for their purposes. The site and data are provided on an "as is" and "as available" basis and Coillte does not guarantee and assumes no legal liability or responsibility for the accuracy, timeliness, completeness, performance or fitness for a particular purpose, of the site or any content. Copyright Declaration You agree not to use the information provided except for research or private study and will not supply a copy of this information to any other person without seeking prior permission from Coillte. You may not use any part of this content for commercial purposes without obtaining permission from Coillte to do so, for which a license may be required. Coillte is the owner or licensee of all intellectual property rights in this layer and such rights are protected by copyright. You acknowledge that data downloaded are subject to change and update. If this information is to be published in any format (written or electronic) you will acknowledge this source and forward a copy of the material in published form to the Coillte office in Newtownmountkennedy or to info@coillte.ie For further information please contact info@coillte.ie

This service shows the datasets listed below. All datasets are in the ITM coordnate system. This data is subject to change and will be updated from time to time. Datasets included in this zip are - Life Sites and Millenium Forest Boundaries . Please refer to terms of use for this dataset before using. These are available below or on the Coillte Public Viewer. The link to this is also included on this page below. Use of data All data on this viewer is available to download and subject to the terms of use – by downloading the data you are agreeing to the terms of use. Data is in ITM format. You agree not to copy, publish or use the data on another website or in any manner likely to confuse members of the public or amount to misrepresentation as to your identity or relationship with Coillte. You agree not to access the data contained therein in any way which is unlawful, illegal, fraudulent or harmful or in connection with any for any unlawful, illegal, fraudulent or harmful activity, including data privacy breaches. The dataset is made available free of charge. We do not guarantee that this dataset, or any content in our Arc GIS online platform, will always be available or be uninterrupted. Coillte may suspend or withdraw or restrict the availability of all or part of the Viewer for business or operational reasons. The content on the Coillte ArcGIS platform is for general information only. Reasonable care has been exercised in the compilation of the information available through the ArcGIS online platform. There is no representation or warranty made as to the accuracy, completeness or currency of such information. The use of any such information, which may be altered or updated at any time without notice, is at the sole risk of the user. Coillte cannot accept responsibility for any errors or omissions or any consequential loss as a result of the same. Before relying on the information on this site, users should carefully evaluate its accuracy, currency, completeness and relevance for their purposes. The site and data are provided on an "as is" and "as available" basis and Coillte does not guarantee and assumes no legal liability or responsibility for the accuracy, timeliness, completeness, performance or fitness for a particular purpose, of the site or any content. Copyright Declaration You agree not to use the information provided except for research or private study and will not supply a copy of this information to any other person without seeking prior permission from Coillte. You may not use any part of this content for commercial purposes without obtaining permission from Coillte to do so, for which a license may be required. Coillte is the owner or licensee of all intellectual property rights in this layer and such rights are protected by copyright. You acknowledge that data downloaded are subject to change and update. If this information is to be published in any format (written or electronic) you will acknowledge this source and forward a copy of the material in published form to the Coillte office in Newtownmountkennedy or to info@coillte.ie For further information please contact info@coillte.ie

This Archaeological Survey of Ireland dataset is published from the database of the National Monuments Service Sites and Monuments Record (SMR). This dataset also can be viewed and interrogated through the online Historic Environment Viewer: https://heritagedata.maps.arcgis.com/apps/webappviewer/index.html?id=0c9eb9575b544081b0d296436d8f60f8 A Sites and Monuments Record (SMR) was issued for all counties in the State between 1984 and 1992. The SMR is a manual containing a numbered list of certain and possible monuments accompanied by 6-inch Ordnance Survey maps (at a reduced scale). The SMR formed the basis for issuing the Record of Monuments and Places (RMP) - the statutory list of recorded monuments established under Section 12 of the National Monuments (Amendment) Act 1994. The RMP was issued for each county between 1995 and 1998 in a similar format to the existing SMR. The RMP differs from the earlier lists in that, as defined in the Act, only monuments with known locations or places where there are believed to be monuments are included. The large Archaeological Survey of Ireland archive and supporting database are managed by the National Monuments Service and the records are continually updated and supplemented as additional monuments are discovered. On the Historic Environment viewer an area around each monument has been shaded, the scale of which varies with the class of monument. This area does not define the extent of the monument, nor does it define a buffer area beyond which ground disturbance should not take place – it merely identifies an area of land within which it is expected that the monument will be located. It is not a constraint area for screening – such must be set by the relevant authority who requires screening for their own purposes. This data has been released for download as Open Data under the DPER Open Data Strategy and is licensed for re-use under the Creative Commons Attribution 4.0 International licence. http://creativecommons.org/licenses/by/4.0 Please note that the centre point of each record is not indicative of the geographic extent of the monument. The existing point centroids were digitised relative to the OSI 6-inch mapping and the move from this older IG-referenced series to the larger-scale ITM mapping will necessitate revisions. The accuracy of the derived ITM co-ordinates is limited to the OS 6-inch scale and errors may ensue should the user apply the co-ordinates to larger scale maps. Records that do not refer to 'monuments' are designated 'Redundant record' and are retained in the archive as they may relate to features that were once considered to be monuments but which on investigation proved otherwise. Redundant records may also refer to duplicate records or errors in the data structure of the Archaeological Survey of Ireland. This dataset is provided for re-use in a number of ways and the technical options are outlined below. For a live and current view of the data, please use the web services or the data extract tool in the Historic Environment Viewer. The National Monuments Service also provide an Open Data snapshot of its national dataset in CSV as a bulk data download. Users should consult the National Monument Service website https://www.archaeology.ie/ for further information and guidance on the National Monument Act(s) and the legal significance of this dataset. Open Data Bulk Data Downloads (version date: 23/08/2023) The Sites and Monuments Record (SMR) is provided as a national download in Comma Separated Value (CSV) format. This format can be easily integrated into a number of software clients for re-use and analysis. The Longitude and Latitude coordinates are also provided to aid its re-use in web mapping systems, however, the ITM easting/northings coordinates should be quoted for official purposes. ERSI Shapefiles of the SMR points and SMRZone polygons are also available The SMRZones represent an area around each monument, the scale of which varies with the class of monument. This area does not define the extent of the monument, nor does it define a buffer area beyond which ground disturbance should not take place – it merely identifies an area of land within which it is expected that the monument will be located. It is not a constraint area for screening – such must be set by the relevant authority who requires screening for their own purposes. GIS Web Service APIs (live views): For users with access to GIS software please note that the Archaeological Survey of Ireland data is also available spatial data web services. By accessing and consuming the web service users are deemed to have accepted the Terms and Conditions. The web services are available at the URL endpoints advertised below: SMR; https://services-eu1.arcgis.com/HyjXgkV6KGMSF3jt/arcgis/rest/services/SMROpenData/FeatureServer SMRZone; https://services-eu1.arcgis.com/HyjXgkV6KGMSF3jt/arcgis/rest/services/SMRZoneOpenData/FeatureServer Historic Environment Viewer - Query Tool The "Query" tool can alternatively be used to selectively filter and download the data represented in the Historic Environment Viewer. The instructions for using this tool in the Historic Environment Viewer are detailed in the associated Help file: https://www.archaeology.ie/sites/default/files/media/pdf/HEV_UserGuide_v01.pdf

WARNINGThis data is provided here for users of specialist GIS software only. The same information is available in a much more user-friendly format in the Services near me page on the main council website, and anyone interested in enrolling a child in school should see the page on Enrolment in Primary and Secondary Schools in DundeeDescriptionThis layer contains 5 sublayers - 1 shows all Dundee City Council Schools, and the other 4 show catchment boundaries in the following categories:Denominational PrimaryNon-denominational (Roman Catholic) PrimaryDenominational SecondaryNon-denominational (Roman Catholic) SecondaryThe Council uses catchment areas to decide where your child is given a place at school. A catchment area is an area around a single school. Children who live in this area are usually offered a place at the school. For more information please see DCC Guidance on Enrolment at P1 and S1 and on Placing Requests (208KB MS Word doc)LimitationsTBDUpdatesThis data is updated as required. This typically happens around October or November before enrolment starts for the next school year each year. The data may therefore reflect the catchments that are due to take effect at the start of the next school year. Usage This layer can be used directly in Web apps like the ArcGIS Online mapviewer, dashboards, storymaps, etc, some of which are available via the council websiteMobile apps like ArcGIS FieldDesktop apps like ArcGIS ProLinks to this layer can also be found in:Dundee Council open data portal - for technical specialists to download and exploring the data Improvement Service Spatial Hub - included in a national dataset that is collated and distributed by IS. One Dundee GIS Portal based on ArcGIS Enterprise - for DCC staff on internal DCC devices - TBDScottish Government spatial data portal - TBDdata.gov.uk - TBDUsage in other softwareThis data is also available as a Web Feature Service (WFS) for use in other GIS software such as QGIS. Integration tipsFor most integration purposes it will be easier to use one of the UPRN based items mentioned below under 'Related data'To see how to query this layer please see the 'API Explorer' or modify the examples below.Integration examplesNote that these examples output in pretty json, but the f parameter can be used to change this to other output formats such plain JSON or HTML List of all schoolsAll catchments for an XY locationRelated DataThis layer is used to create the following items for use in system integrations:UPRNs with school catchments - map layer intended for use in live integrations like Firmstep\Granicus. This can be queried to provide all the relevant catchments for a UPRN without needing to know the XY coordinates.UPRN to school catchment seedcode lookup tables - collection of CSV files intended for use in disconnected integrations like SEEMIS, but may also be used to remove dependency on a live integration in Firmstep/Granicus.

This dataset contains model-based county-level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2020 or 2019 county population estimates, and American Community Survey (ACS) 2016–2020 or 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census 2020 county boundary file in a GIS system to produce maps for 29 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 29 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software.

https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This CED spatial web service (ESRI ArcGIS Online Hosted Feature Layer) is a optimized quick visualization and unique value source for optimized CED web startup. The CED provides Sagebrush biome spatial representations and attribute information of conservation efforts entered into the Conservation Efforts Database (https://conservationefforts.org) by various data providers. This spatial web service is made of point and polygon layers and non-spatial tables. Feature records are group with their respective spatial feature type layers (point, polygon). The two spatial layers have identical attribute fields.Read only access to this data is ONLY available via an interactive web map on the Conservation Efforts Database website or authorized websites. Users who are interested in more access can directly contact the data providers by using the contact information available through the CED interactive map's pop-up/identify feature.The spatially explicit, web-based Conservation Efforts Database is capable of (1) allowing multiple-users to enter data from different locations, (2) uploading and storing documents, (3) linking conservation actions to one or more threats (one-to-many relationships), (4) reporting functions that would allow summaries of the conservation actions at multiple scales (e.g., management zones, populations, or priority areas for conservation), and (5) accounting for actions at multiple scales from small easements to statewide planning efforts.The sagebrush ecosystem is the largest ecosystem type in the continental U.S., providing habitat for more than 350 associated fish and wildlife species. In recognition of the need to conserve a healthy sagebrush ecosystem to provide for the long-term conservation of its inhabitants, the US Fish and Wildlife Service (Service) and United States Geological Survey (USGS) developed the Conservation Efforts Database version 2.0.0 (CED). The purpose of the CED is to efficiently capture the unprecedented level of conservation plans and actions being implemented throughout the sagebrush ecosystem and designed to capture actions not only for its most famous resident, the greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) but for the other species that rely on sagebrush habitats. Understanding the distribution and type of conservation actions happening across the landscape will allow visualization and quantification of the extent to which threats are being addressed.The purpose of this CED spatial web service (ESRI ArcGIS Online Hosted Feature Layer) is to provide CED data for authorized web sites or authorized users.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at https://goto.arcgisonline.com/landscape11/USA_Soils_Hydric_Class.Hydric soils are soils that form under conditions of saturation, flooding, or ponding long enough during the growing season to develop anaerobic conditions in the upper part of the soil. Hydric soils are poorly or very poorly drained and under natural conditions, these soils are either saturated or inundated long enough during the growing season to support the growth and reproduction of wetland vegetation. Hydric soils are part of the legal definition for wetlands in the United States and are used to identify wetland areas that require a permit issued by the Army Corps of Engineers under Section 404 of the Clean Water Act prior to any ground disturbing activities. For more information on hydric soils see the Natural Resources Conservation Service’s publication Field Indicators of Hydric Soils in the United States.Dataset SummaryPhenomenon Mapped: Hydric soilsUnits: PercentCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: July 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for hydric class is derived from the gSSURGO map unit aggregated attribute table field Hydric Classification - Presence (hydclprs).What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "hydric" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "hydric" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

USA Cropland is a time-enabled imagery layer of the USDA Cropland Data Layer dataset from the National Agricultural Statistics Service (NASS). The time series shows the crop grown during every growing season in the conterminous US since 2008. Use the time slider to select only one year to view or analyze. Press play to see each growing season displayed sequentially in an animated map. The USDA is now serving the Cropland Data Layer in their own application called CroplandCros which allows selection and display of a single product or growing season. This application will eventually replace their popular CropScape application. Dataset SummaryVariable mapped: Crop grown in each pixel since 2008.Data Projection: AlbersMosaic Projection: AlbersExtent: Conterminous USACell Size: 30m in 2008-2023, 10m in 2024Source Type: ThematicVisible Scale: All scales are visibleSource: USDA NASSPublication Date: 2/26/2025 Why USA Cropland living atlas layer masks out NLCD land cover in its default templateUSDA Cropland Data Layer, by default as downloaded from USDA, fills in the non-cultivated areas of the conterminous USA with land cover classes from the MRLC National Land Cover Dataset (NLCD). The default behavior for Esri"s USA Cropland layer is a little bit different. By default the Esri USA Cropland layer uses the analytic renderer, which masks out this NLCD data. Why did we choose to mask out the NLCD land cover classes by default? While crops are updated every year from USDA NASS, the NLCD data changes every several years, and it can be quite a bit older than the crop data beside it. If analysis is conducted to quantify landscape change, the NLCD-derived pixels will skew the results of the analysis because NLCD land cover in a yearly time series may appear to remain the same class for several years in a row. This can be problematic because conclusions drawn from this dataset may underrepresent the amount of change happening to the landscape. To display the most current land cover available from both sources, add both the USA NLCD Land Cover service and USA Cropland time series to your map. Use the analytical template with the USA Cropland service, and draw it on top of the USA NLCD Land Cover service. When a time slider is used with these datasets together, the map user will see the most current land cover from both services in any given year. This layer and the data making up the layer are in the Albers map projection. Albers is an equal area projection, and this allows users of this layer to accurately calculate acreage without additional data preparation steps. This also means it takes a tiny bit longer to project on the fly into web Mercator, if that is the destination projection of the layer. Processing templates available with this layerTo help filter out and display just the crops and land use categories you are interested in showing, choose one of the thirteen processing templates that will help you tailor the symbols in the time series to suit your map application. The following are the processing templates that are available with this layer: Analytic RendererUSDA Analytic RendererThe analytic renderer is the default template. NLCD codes are masked when using analytic renderer processing templates. There is a default esri analytic renderer, but also an analytic renderer that uses the original USDA color scheme that was developed for the CropScape layers. This is useful if you have already built maps with the USDA color scheme or otherwise prefer the USDA color scheme. Cartographic RendererUSDA Cartographic RendererThese templates fill in with NLCD land cover types where crops are not cultivated, thereby filling the map with color from coast to coast. There is also a template using the USDA color scheme, which is identical to the datasets as downloaded from USDA NASS. In addition to different ways to display the whole dataset, some processing templates are included which help display the top agricultural products in the United States. If these templates seem to include too many crops in their category (for example, tomatoes are included in both the fruit and vegetables templates), this is because it"s easier for a map user to remove a symbol from a template than it is to add one. Corn - Corn, sweet corn, popcorn or ornamental corn, plus double crops with corn and another crop.Cotton - Cotton and double crops, includes double crops with cotton and another crop.Fruit - Symbolized fruit crops include not only things like melons, apricots, and strawberries, but also olives, avocados, and tomatoes.Nuts - Peanuts, tree nuts, sunflower, etc.Oil Crops - Oil crops include rapeseed and canola, soybeans, avocado, peanut, corn, safflower, sunflower, also cotton and grapes.Permanent Crops - Crops that do not need to be replanted after harvest. Includes fruit and nut trees, caneberries, and grapes.Rice - Rice crops.Sugar - Crops grown to make sugars. Sugar beets and cane are displayed of course, but so are corn and grapes.Soybeans - Soybean crops. Includes double crops where soybeans are grown at some time during the growing season.Vegetables - Vegetable crops, and yes this includes tomatoes.Wheat - Winter and spring wheat, durum wheat, triticale, spelt, and wheat double crops. In many places, two crops were grown in one growing season. Keep in mind that a double crop of corn and soybeans will display in both the corn and soybeans processing templates. What can you do with this layer?This layer is suitable for both visualization and analysis acrossthe ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application. Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "USA Cropland" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "USA Cropland" in the search box, browse to the layer then click OK. In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. Online you can filter the layer to show subsets of the data using the filter button and the layer"s built-in raster functions. The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one. Index to raster values in USA Cropland:Value,Crop0,Background (not a cultivated crop or no data)1,Corn2,Cotton3,Rice4,Sorghum5,Soybeans6,Sunflower10,Peanuts11,Tobacco12,Sweet Corn13,Popcorn or Ornamental Corn14,Mint21,Barley22,Durum Wheat23,Spring Wheat24,Winter Wheat25,Other Small Grains26,Double Crop Winter Wheat/Soybeans27,Rye28,Oats29,Millet30,Speltz31,Canola32,Flaxseed33,Safflower34,Rape Seed35,Mustard36,Alfalfa37,Other Hay/Non Alfalfa38,Camelina39,Buckwheat41,Sugarbeets42,Dry Beans43,Potatoes44,Other Crops45,Sugarcane46,Sweet Potatoes47,Miscellaneous Vegetables and Fruits48,Watermelons49,Onions50,Cucumbers51,Chick Peas52,Lentils53,Peas54,Tomatoes55,Caneberries56,Hops57,Herbs58,Clover/Wildflowers59,Sod/Grass Seed60,Switchgrass61,Fallow/Idle Cropland62,Pasture/Grass63,Forest64,Shrubland65,Barren66,Cherries67,Peaches68,Apples69,Grapes70,Christmas Trees71,Other Tree Crops72,Citrus74,Pecans75,Almonds76,Walnuts77,Pears81,Clouds/No Data82,Developed83,Water87,Wetlands88,Nonagricultural/Undefined92,Aquaculture111,Open Water112,Perennial Ice/Snow121,Developed/Open Space122,Developed/Low Intensity123,Developed/Med Intensity124,Developed/High Intensity131,Barren141,Deciduous Forest142,Evergreen Forest143,Mixed Forest152,Shrubland176,Grassland/Pasture190,Woody Wetlands195,Herbaceous Wetlands204,Pistachios205,Triticale206,Carrots207,Asparagus208,Garlic209,Cantaloupes210,Prunes211,Olives212,Oranges213,Honeydew Melons214,Broccoli215,Avocados216,Peppers217,Pomegranates218,Nectarines219,Greens220,Plums221,Strawberries222,Squash223,Apricots224,Vetch225,Double Crop Winter Wheat/Corn226,Double Crop Oats/Corn227,Lettuce228,Double Crop Triticale/Corn229,Pumpkins230,Double Crop Lettuce/Durum Wheat231,Double Crop Lettuce/Cantaloupe232,Double Crop Lettuce/Cotton233,Double Crop Lettuce/Barley234,Double Crop Durum Wheat/Sorghum235,Double Crop Barley/Sorghum236,Double Crop Winter Wheat/Sorghum237,Double Crop Barley/Corn238,Double Crop Winter Wheat/Cotton239,Double Crop Soybeans/Cotton240,Double Crop Soybeans/Oats241,Double Crop Corn/Soybeans242,Blueberries243,Cabbage244,Cauliflower245,Celery246,Radishes247,Turnips248,Eggplants249,Gourds250,Cranberries254,Double Crop Barley/Soybeans Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Office for National Statistics' national and subnational Census 2021.This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their method used to travel to work (2001 specification). The estimates are as at Census Day, 21 March 2021.Census 2021 took place during a period of rapid change. We gave extra guidance to help people on furlough answer the census questions about work. However, we are unable to determine how furloughed people followed the guidance. Take care when using this data for planning purposes. Read more about specific quality considerations in our Labour market quality information for Census 2021 methodology Method of travel to workplace definition: A person's place of work and their method of travel to work. This is the 2001 method of producing travel to work variables.'Work mainly from home' applies to someone who indicated their place of work as their home address and travelled to work by driving a car or van, for example visiting clients.Quality information: As Census 2021 was during a unique period of rapid change, take care when using this data for planning purposes.Comparability with 2011: Not comparable. It is difficult to compare this variable with the 2011 Census because Census 2021 took place during a national lockdown. The government advice at the time was for people to work from home (if they can) and avoid public transport.People who were furloughed (about 5.6 million) were advised to answer the transport to work question based on their previous travel patterns before or during the pandemic. This means that the data does not accurately represent what they were doing on Census Day. This variable cannot be directly compared with the 2011 Census Travel to Work data as it does not include people who were travelling to work on that day. It may however, be partially compared with bespoke tables from 2011. This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at https://goto.arcgisonline.com/landscape11/USA_Soils_Hydrologic_Group.When rain falls over land, a portion of it runs off into stream channels and storm water systems while the remainder infiltrates into the soil or returns to the atmosphere directly through evaporation.Physical properties of soil affect the rate that water is absorbed and the amount of runoff produced by a storm. Hydrologic soil group provides an index of the rate that water infiltrates a soil and is an input to rainfall-runoff models that are used to predict potential stream flow.For more information on using hydrologic soil group in hydrologic modeling see the publication Urban Hydrology for Small Watersheds (Natural Resources Conservation Service, United States Department of Agriculture, Technical Release–55).Dataset SummaryPhenomenon Mapped: Soil hydrologic groupUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: July 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for hydrologic group is derived from the gSSURGO map unit aggregated attribute table field Hydrologic Group - Dominant Conditions (hydgrpdcd).The seven classes of hydrologic soil group followed by definitions:Group A - Group A soils consist of deep, well drained sands or gravelly sands with high infiltration and low runoff rates.Group B - Group B soils consist of deep well drained soils with a moderately fine to moderately coarse texture and a moderate rate of infiltration and runoff.Group C - Group C consists of soils with a layer that impedes the downward movement of water or fine textured soils and a slow rate of infiltration.Group D - Group D consists of soils with a very slow infiltration rate and high runoff potential. This group is composed of clays that have a high shrink-swell potential, soils with a high water table, soils that have a clay pan or clay layer at or near the surface, and soils that are shallow over nearly impervious material.Group A/D - Group A/D soils naturally have a very slow infiltration rate due to a high water table but will have high infiltration and low runoff rates if drained.Group B/D - Group B/D soils naturally have a very slow infiltration rate due to a high water table but will have a moderate rate of infiltration and runoff if drained.Group C/D - Group C/D soils naturally have a very slow infiltration rate due to a high water table but will have a slow rate of infiltration if drained.What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "soil hydrologic group" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "soil hydrologic group" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at https://goto.arcgisonline.com/landscape11/USA_Soils_Drainage_Class.Soils vary widely in their ability to retain or drain water. The rate at which water drains into the soil has a direct effect on the amount and timing of runoff, what crops can be grown, and where wetlands form. In soils with low drainage rates water will pond on the soil's surface. Poorly drained soils are desirable when growing crops like rice where the fields are flooded for cultivation but other crops need better drained soils.Dataset SummaryPhenomenon Mapped: Drainage Class of SoilsUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: July 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for drainage class is derived from the gSSURGO map unit aggregated attribute table field Drainage Class - Dominant Condition (drclassdcd).The layer has an attribute field for Drainage Class and a description field for use in pop-ups. The eight values of drainage class with corresponding attribute table index value are defined by the NRCS Soil Survey Manual as:0. Excessively drained: Water is removed very rapidly. The occurrence of internal free water commonly is very rare or very deep. The soils are commonly coarse-textured and have very high hydraulic conductivity or are very shallow.1. Somewhat excessively drained: Water is removed from the soil rapidly. Internal free water occurrence commonly is very rare or very deep. The soils are commonly coarse-textured and have high saturated hydraulic conductivity or are very shallow.2. Well drained: Water is removed from the soil readily but not rapidly. Internal free water occurrence commonly is deep or very deep; annual duration is not specified. Water is available to plants throughout most of the growing season in humid regions. Wetness does not inhibit growth of roots for significant periods during most growing seasons. The soils are mainly free of the deep to redoximorphic features that are related to wetness.3. Moderately well drained: Water is removed from the soil somewhat slowly during some periods of the year. Internal free water occurrence commonly is moderately deep and transitory through permanent. The soils are wet for only a short time within the rooting depth during the growing season, but long enough that most mesophytic crops are affected. They commonly have a moderately low or lower saturated hydraulic conductivity in a layer within the upper 1 m, periodically receive high rainfall, or both.4. Somewhat poorly drained: Water is removed slowly so that the soil is wet at a shallow depth for significant periods during the growing season. The occurrence of internal free water commonly is shallow to moderately deep and transitory to permanent. Wetness markedly restricts the growth of mesophytic crops, unless artificial drainage is provided. The soils commonly have one or more of the following characteristics: low or very low saturated hydraulic conductivity, a high water table, additional water from seepage, or nearly continuous rainfall.5. Poorly drained: Water is removed so slowly that the soil is wet at shallow depths periodically during the growing season or remains wet for long periods. The occurrence of internal free water is shallow or very shallow and common or persistent. Free water is commonly at or near the surface long enough during the growing season so that most mesophytic crops cannot be grown, unless the soil is artificially drained. The soil, however, is not continuously wet directly below plow-depth. Free water at shallow depth is usually present. This water table is commonly the result of low or very low saturated hydraulic conductivity of nearly continuous rainfall, or of a combination of these.6. Very poorly drained: Water is removed from the soil so slowly that free water remains at or very near the ground surface during much of the growing season. The occurrence of internal free water is very shallow and persistent or permanent. Unless the soil is artificially drained, most mesophytic crops cannot be grown. The soils are commonly level or depressed and frequently ponded. If rainfall is high or nearly continuous, slope gradients may be greater.7. Subaqueous Soils: These soils are under the surface of a body of water. (There are only a few of these in the entire dataset.)What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "drainage class" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "drainage class" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at http://goto.arcgisonline.com/earthobs2/REMSS_SeaSurfaceTempSea Surface Temperature is a key climate and weather measurement used for weather prediction, ocean forecasts, tropical cyclone forecasts, and in coastal applications such as fisheries, pollution monitoring and tourism. El Niño and La Niña are two examples of climate events which are forecast through the use of sea surface temperature maps. The Naval Oceanographic Office sea surface temperature dataset is calculated from satellite-based microwave and infrared imagery. These data are optimally interpolated to provide a daily, global map of the midday (12:00 pm) sea surface temperature. Learn more about the source data. Phenomenon Mapped: Sea Surface TemperatureUnits: Degrees CelsiusTime Interval: DailyTime Extent: 2008/04/01 12:00:00 UTC to presentCell Size: 11 kmSource Type: ContinuousPixel Type: Floating PointData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: Global OceansSource: Naval Oceanographic OfficeUpdate Cycle: SporadicArcGIS Server URL: http://earthobs2.arcgis.com/arcgisTime: This is a time-enabled layer. It shows the average sea surface temperature during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the average of all days in the time extent. Minimum temporal resolution is one day; maximum is one month.What can you do with this layer?Visualization: This layer can be used for visualization online in web maps and in ArcGIS Desktop.Analysis: This layer can be used as an input to geoprocessing tools and model builder. Units are in degrees Celsius, and there is a processing template to convert pixels to Fahrenheit. See this Esri blog post for more information on how to use this layer in your analysis. Do not use this layer for analysis while the Cartographic Renderer processing template is applied.This layer is part of the Living Atlas of the World that provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.

Office for National Statistics' national and subnational Census 2021. This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in employment the week before the census in England and Wales by the distance they travelled to work. The estimates are as at Census Day, 21 March 2021.Census 2021 took place during a period of rapid change. We gave extra guidance to help people on furlough answer the census questions about work. However, we are unable to determine how furloughed people followed the guidance. Take care when using this data for planning purposes. Read more about specific quality considerations in our Labour market quality information for Census 2021 methodology Distance travelled to work definition: The distance, in kilometres, between a person's residential postcode and their workplace postcode measured in a straight line. A distance travelled of 0.1km indicates that the workplace postcode is the same as the residential postcode. Distances over 1200km are treated as invalid, and an imputed or estimated value is added.Work mainly at or from home: is made up of those that ticked either the 'Mainly work at or from home' box for the address of workplace question, or the Work mainly at or from home box for the method of travel to work question.Other: includes no fixed place of work, working on an offshore installation and working outside of the UK.Distance is calculated as the straight line distance between the enumeration postcode and the workplace postcode.Quality information: As Census 2021 was during a unique period of rapid change, take care when using this data for planning purposes.Comparability with 2011: Not comparable. It is difficult to compare this variable with the 2011 Census because Census 2021 took place during a national lockdown. The government advice at the time was for people to work from home (if they can) and avoid public transport.Only those who work at a workplace or depot gave their workplace address. This means that the number of people who answered this question is a significantly smaller proportion of the population than normal.People who were on furlough (about 5.6 million), could have given details based on their patterns before or during the pandemic, or what they did during the census taking place, including Census Day. This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.

The Provincial Digital Elevation Model (PDEM) is a general-purpose dataset designed to represent true ground elevation where possible and is based on best-available data across the province. This dataset has not been conditioned for any specific application. Please see the User Guide below for more information. Zoom in on the map and click your area of interest to determine which package(s) you require for download. Now also available through a web service which exposes the data for visualization and geoprocessing. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection. For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca. Service Endpointshttps://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_Provincial_Digital_Elevation_Model/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_Provincial_Digital_Elevation_Model/ImageServer (Government of Ontario Internal Users)Additional DocumentationProvincial Digital Elevation Model - User Guide (Word) Provincial Digital Elevation Model - Methods and Processes (Word) Updating Provincial Elevation Data Using Least Cost Path Analysis (Word) Provincial Digital Elevation Model - Boundary in shape file format (Shapefile) OBM Photo Block Index (Zip file) PDEM Spatial Metadata Index (Elevation Source) - August 11th, 2025 (Zip file) Product PackagesProvincial Digital Elevation Model -North (CGVD28) Provincial Digital Elevation Model - South (CGVD28) Provincial Digital Elevation Model - North (CGVD2013)Provincial Digital Elevation Model - South (CGVD2013)StatusOn going: Data is continually being updated Maintenance and Update Frequency As needed: Data is updated as deemed necessary RSS FeedFollow our feed to get the latest announcements and developments concerning our PDEM product. Visit our feed at the bottom of our ArcGIS Online PDEM page. Contact Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at https://goto.arcgisonline.com/landscape11/USA_Soils_Available_Water_Storage.The amount of water in soil is based on rainfall amount, what proportion of rain infiltrates into the soil, and the soil's storage capacity. Available water storage is the maximum amount of plant available water a soil can provide. It is an indicator of a soil’s ability to retain water and make it sufficiently available for plant use. Available Water Storage is a capacity estimate for the top 150 centimeters of soil. It is calculated from the difference between soil water content at field capacity and the permanent wilting point adjusted for salinity and fragments.Available water storage is used to develop water budgets, predict droughtiness, design and operate irrigation systems, design drainage systems, protect water resources, and predict yields. Available water storage is an important input into hydrologic models including the Soil and Water Assessment Tool (SWAT) - a water quality model that is designed to assess non-point and point source pollution at the river basin scale. Available water storage can also be used as an indication of a soil's drought susceptibility, for water recharge modeling, to assess a soil's ability to support crops, and for many other purposes.Dataset SummaryPhenomenon Mapped: Amount of water a soil can hold, that is available to plantsUnits: MillimetersCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: July 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for available water storage is derived from the gSSURGO map unit aggregated attribute table field Available Water Storage 0-150cm Weighted Average (aws0150wta).What can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "available water storage" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "available water storage" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at http://goto.arcgisonline.com/landscape6/World_Bioclimates.Climate plays a major role in determining the distribution of plants and animals. Bioclimatology, the study of climate as it affects and is affected by living organisms, is key to understanding the patterns of forests and deserts on the landscape, where productive agricultural lands may be found, and how changes in the climate will affect rare species. This layer is part of the Ecophysiographic Project and is one of the four input layers used to create the World Ecological Land Units Map.Dataset Summary This layer provides access to a 250m cell-sized raster with a bioclimatic stratification. The source dataset was a 30-arcsecond resolution raster (equivalent to 0.86 km2 at the equator or about a 920m pixel size). The layer has the following attributes: Temperature Description - Seven classes based on the number of growing degree days (the monthly mean temperature multiplied by number of days in the month summed for all months). The 1950 to 2000 monthly average temperature was used to calculate growing degree days. Values in this field and associated number of growing degree days are:Temperature DescriptionGrowing Degree DaysVery Hot9,000 – 13,500Hot7,000 – 9,000Warm4,500 – 7,000Cool2,500 – 4,500Cold1,000 – 2,500Very Cold300 – 1,000Arctic0 - 300Aridity Description - Six classes based on an index of aridity calculated by dividing precipitation by evapotranspiration. Precipitation and evapotranspiration are average values from 1950 to 2000.Aridity DescriptionAridity IndexVery Wet1.5 – 70Wet1.0 – 1.5Moist0.6 – 1.0Semi-dry0.3 – 0.6Dry0.1 – 0.3Very Dry0.01 – 0.1Bioclimate Class - a 2-part description that combines the value of the Temperature Description field and the Aridity Description field. The alias for this field is ELU Bioclimate Reclass. This layer was created by modifying the dataset documented in the publication: Metzger and others. 2012. A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring. What can you do with this layer? This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. A service is available providing access to the data table associated with this layer. The data table services can be used by developers to quickly and efficiently query the data and to create custom applications. For more information see the World Ecophysiographic Tables.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

SSURGO PortalThe newest version of SSURGO Portal with Soil Data Viewer is available via the Quick Start Guide. Install Python to C:\Program Files. This is a different version than what ArcGIS Pro uses.If you need data for multiple states, we also offer a prebuilt large database with all SSURGO for the entire United States and all Islands. The prebuilt saves you time but it’s large and takes a while to download.You can also use the prebuilt gNATSGO GeoPackage database in SSURGO Portal – Soil Data Viewer. Read the ReadMe.txt in the folder. More about gNATSGO here. You can also import STATSGO2 data into SSURGO Portal and create a database to use in Soil Data Viewer – Available for download via the Soils Box folder. SSURGO Portal NotesThis 10 minute video covers it all, other than installation of SSURGO Portal and the GIS tool. Installation is typically smooth and easy.There is also a user guide on the SSURGO Portal website that can be very helpful. It has info about using the data in ArcGIS Pro or QGIS. SQLite SSURGO database be opened and queried with DB Browser. It’s essentially free Microsoft Access.Guidance about setting up DB Browser to easily open SQLite databases is available in section 4 of this Installation Guide.Workflow if you need to make your own databaseInstall SSURGO PortalInstall SSURGO Downloader GIS tool (Refer to the Installation and User Guide for assistance)There is one for QGIS and one for ArcGIS Pro. They both do the same thing. Quickly download California SSURGO data with toolEnter two digit state symbol followed by asterisk in “Search by Areasymbol” to download all data for state.For example, enter CA* to batch download all data for CaliforniaOpen SSURGO Portal and create a new SQLite SSURGO Template database (Refer to the User Guide for assistance)Import SSURGO data you downloaded into databaseYou can import SSURGO data from many states at once, building a database that spans many statesAfter SSURGO data is done importing, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a map (Refer to the User Guide for assistance)Workflow if you need use large prebuilt database (don’t make own database) Install SSURGO PortalIn SSURGO Portal, browse to unzipped prebuilt GeoPackage database with all SSURGOprebuilt large database with all SSURGOgNATSGO GeoPackage databaseIn SSURGO Portal, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a mapIf you have trouble installing SSURGO Portal. Its usually the connection with Python. Create Desktop short cut that tells SSURGO Portal which Python to useThese were created for Windows 11 Right click anywhere on your desktop and choose New > ShortcutIn the text bar enter your path to the python.exe and your path to the SSURGO Portal.pyz. Notes:Example of format:"C:\Program Files\Python310\python.exe" "C:\SSURGO Portal\SSURGO_Portal-0.3.0.8.pyz"Include quotation marks.Paths may be different on your machine. To avoid typing, you can browse to python.exe in windows explorer, right click and select "Copy as Path and paste results into box. Paste into short location and then do the same for SSURGO Portal.pyz file, but paste to the right of the python.exe path. Click NextName the shortcut anything you want.