NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.

Thank you for your interest in DWR land use datasets.

The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.

Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.

For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.

For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.

Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the physical soil variable percent sand (sand).Within the subset of soil that is smaller than 2mm in size, also known as the fine earth portion, sand is defined as the particles that are greater than 0.05mm. Sand provides excellent aeration and drainage, but has a low capacity for holding water and nutrients.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for sand are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Proportion of sand particles (> 0.05 mm) in the fine earth fraction in g/100g (%).Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for sand were used to create this layer. You may access the percent sand in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat 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 "world soils soilgrids" 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 "world soils soilgrids" 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.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

This data set is part of a time series for the years 1700, 1800, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.The Anthropogenic Biomes of the World, Version 2 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization. Potential natural vegetation, biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. Also includes Version 1:The Anthropogenic Biomes of the World, Version 1 data set describes globally-significant ecological patterns within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture, urbanization, forestry and other land uses. Conventional biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate. Now that humans have fundamentally altered global patterns of ecosystem form, process, and biodiversity, anthropogenic biomes provide a contemporary view of the terrestrial biosphere in its human-altered form. Anthropogenic biomes may also be termed "anthromes" to distinguish them from conventional biome systems, or "human biomes" (a simpler but less precise term).This data set is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The vector (polygon) map is in digital format within a geodatabase structure that allows for complex relationships to be established between spatial and tabular data, and allows much of the data to be accessed concurrently. Strict nomenclature was enforced for polygons and a unique name was assigned to each polygon. These reflected the verified physiognomic formation type by a prefix of representative letters (e.g., W = Woodland, SS = shrub savanna), followed by a number. Using ArcMap, polygon boundaries were buffered and excluded based on the distance equal to the radius of the selected plot size, positional accuracy of the map, and positional error of the GPS to be used by the assessment crew (Lea and Curtis 2010). The resulting polygons were converted to raster format and points were distributed using the “distribute spatially balanced points” function in ArcToolbox. This function uses the RRQRR algorithm (Theobald et al. 2007) to distribute spatially balanced points throughout the raster. Next, each point was buffered using the radius of the assigned plot size to create a circular area (see Figure 3-1) that was later used as a visual aid to delineate the survey area. These circular plot areas (polygons, essentially) and the plot centroids for all map classes were merged and assigned a unique identifier. All information was removed that could give an assessor any indication as to which class it belonged.

Wetlands are areas where water is present at or near the surface of the soil during at least part of the year. Wetlands provide habitat for many species of plants and animals that are adapted to living in wet habitats. Wetlands form characteristic soils, absorb pollutants and excess nutrients from aquatic systems, help buffer the effects of high flows, and recharge groundwater. Data on the distribution and type of wetland play an important role in land use planning and several federal and state laws require that wetlands be considered during the planning process.The National Wetlands Inventory (NWI) was designed to assist land managers in wetland conservation efforts. The NWI is managed by the US Fish and Wildlife Service.Dataset SummaryPhenomenon Mapped: WetlandsUnits: MetersCell Size: 10 metersSource Type: ThematicPixel Type: Unsigned integer 16 bitData Coordinate System: North America Albers Equal Area Conic (WKID 102008)Mosaic Projection: North America Albers Equal Area Conic (WKID 102008)Extent: 50 United States plus Puerto Rico, American Samoa, the US Virgin Islands, the Northern Mariana Islands, and US Minor Outlying IslandsSource: U.S. Fish and Wildlife ServicePublication Date: October 26, 2024 ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/This layer was created from the October 26, 2024 version of the NWI. The original NWI features were downloaded from USFWS and then converted to a single part feature class using the Multipart To Singlepart tool. After that, the Dice tool was used to break up features larger than 50,000 vertices. The diced, singlepart features were projected to North America Albers projection, then the Repair Geometry tool was run on the features, using tool defaults, to prepare it for a clean rasterization. The features were then converted to several rasters in North America Albers projection using the Polygon to Raster Tool. The National Land Cover Dataset was used as a snap raster for the rasterization process. The rasters representing different parts of the USA are served together as a single layer from a mosaic dataset on the server.This layer includes attributes from the original dataset as well as attributes added by Esri for use in the default pop-up and to allow the user to query and filter the data. NWI derived attributes:Wetland Code - a code that identifies specific attributes of the wetlandWetland Type - one of 8 wetland typesEsri created attributes:System - code indicating the system and subsystem of the wetlandClass - code indicating the class and subclass of the wetlandModifier 1, Modifier 2, Modifier 3, Modifier 4 - these four fields contain letter codes for modifiers applied to the wetland descriptionSystem Name - the name of the system (Marine, Estuarine, Riverine, Lacustrine, or Palustrine)Subsystem Name - the name of the subsystemClass Name - the name of the classSubclass Name - the name of the subclassModifier 1 Name, Modifier 2 Name, Modifier 3 Name , Modifier 4 Name - these four fields contain names for modifiers applied to the wetland descriptionPopup Header - this field contains a text string that is used to create the header in the default pop-up System Text - this field contains a text string that is used to create the system description text in the default pop-upClass Text - this field contains a text string that is used to create the class description text in the default pop-upModifier Text - this field contains a text string that is used to create the modifier description text in the default pop-upSpecies Text - this field contains a text string that is used to create the species description text in the default pop-upCodes, names, and text fields were derived from the publication Classification of Wetlands and Deepwater Habitats of the United States.The layer serves an index value from a mosaic dataset on the enterprise server. It uses an attribute table function on the mosaic to serve the attributes that appear in the popup for the layer. Because there are more than 2,000 integer values served by the layer, most map clients can not render a legend for this layer. A colormap is used after the attribute table function on the mosaic dataset to help the layer render in the colors intended for the layer.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 "USA Wetlands" 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 Wetlands" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.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.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable nitrogen (nitrogen).Nitrogen is an essential nutrient for sustaining life on Earth. Nitrogen is a core component of amino acids, which are the building blocks of proteins, and of nucleic acids, which are the building blocks of genetic material (RNA and DNA).This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for nitrogen are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Total nitrogen (N) in g/kgCell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for nitrogen were used to create this layer. You may access nitrogen values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat 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 "world soils soilgrids" 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 "world soils soilgrids" 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.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable organic carbon density (ocd) which measures carbon mass in proportion to volume of soil (mass divided by volume.)From Agriculture Victoria: Soil carbon provides a source of nutrients through mineralisation, helps to aggregate soil particles (structure) to provide resilience to physical degradation, increases microbial activity, increases water storage and availability to plants, and protects soil from erosion.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for organic carbon density are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Organic carbon density in kg/m³Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for ocd were used to create this layer. You may access organic carbon density values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat 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 "world soils soilgrids" 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 "world soils soilgrids" 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.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

The GIS Department has now created an Open Data Site for the free distribution of GIS Data. This site allows you to search for layers by key words or by themes. You can download the data in Excel spreadsheet format, or via ArcGIS Shapefile format. You can also filter the selection prior to downloading the data. Additionally, we have links to our public facing Mapping websites and story boards.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable soil organic carbon (soc) which measures the mass of carbon in proportion to the mass of the soil. (mass divided by mass.)From Agriculture Victoria: Soil carbon provides a source of nutrients through mineralisation, helps to aggregate soil particles (structure) to provide resilience to physical degradation, increases microbial activity, increases water storage and availability to plants, and protects soil from erosion.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for soil organic carbon are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Soil organic carbon content in the fine earth fraction in g/kgCell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for soc were used to create this layer. You may access soil organic carbon values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat 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 "world soils soilgrids" 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 "world soils soilgrids" 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.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

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.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the physical soil variable percent silt (silt).Within the subset of soil that is smaller than 2mm in size, also known as the fine earth portion, silt is defined as particles that are equal to or are between 0.002mm and 0.05mm in size. Silty soils are usually more fertile than other types of soil, with a good balance of air circulation and water retention.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for silt are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Proportion of silt particles (≥ 0.002 mm and ≤ 0.05 mm) in the fine earth fraction in g/100g (%)Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for silt were used to create this layer. You may access the percent silt in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat 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 "world soils soilgrids" 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 "world soils soilgrids" 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.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

Summary: Mini Lesson MapStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 3: Standard 3-ESS2-1 - Earth’s Systems - Represent data in tables and graphical displays to describe typical weather conditions expected during a particular seasonGrade level(s) 4: Standard 4-PS3-2 - Energy - Make observations to provide evidence that energy can be transferred from place to place by sound, light, heat, and electric currentsGrade level(s) 4: Standard 4-ESS2-2 - Earth’s Systems - Analyze and interpret data from maps to describe patterns of Earth’s featuresGrade level(s) 5: Standard 5-ESS1-2 - Earth’s Place in the Universe - Represent data in graphical displays to reveal patterns of daily changes in length and direction of shadows, day and night, and the seasonal appearance of some stars in the night skyGrade level(s) 5: Standard 5-ESS2-1 - Earth’s Systems - Develop a model using an example to describe ways the geosphere, biosphere, hydrosphere, and/or atmosphere interact.Grade level(s) 6-8: Standard MS-ESS1-1 - Earth’s Place in the Universe - Develop and use a model of the Earth-sun-moon system to describe the cyclic patterns of lunar phases, eclipses of the sun and moon, and seasonsGrade level(s) 6-8: Standard MS-ESS1-4 - Earth’s Place in the Universe - Construct a scientific explanation based on evidence from rock strata for how the geologic time scale is used to organize Earth’s 4.6-billion-year-old historyGrade level(s) 6-8: Standard MS-ESS2-3 - Earth’s Systems - Analyze and interpret data on the distribution of fossils and rocks, continental shapes, and seafloor structures to provide evidence of the past plate motions.Grade level(s) 6-8: Standard MS-ESS2-3 - Earth’s Systems - Analyze and interpret data on the distribution of fossils and rocks, continental shapes, and seafloor structures to provide evidence of the past plate motions.Grade level(s) 6-8: Standard MS-ESS2-6 - Earth’s Systems - Develop and use a model to describe how unequal heating and rotation of the Earth cause patterns of atmospheric and oceanic circulation that determine regional climates.Grade level(s) 9-12: Standard HS-LS2-6 - Ecosystems: Interactions, Energy, and Dynamics - Evaluate claims, evidence, and reasoning that the complex interactions in ecosystems maintain relatively consistent numbers and types of organisms in stable conditions, but changing conditions may result in a new ecosystem. [Grade level(s) 9-12: Standard HS-LS4-4 - Biological Evolution: Unity and Diversity - Construct an explanation based on evidence for how natural selection leads to adaptation of populationsGrade level(s) 9-12: Standard HS-ESS1-5 - Earth’s Place in the Universe - Evaluate evidence of the past and current movements of continental and oceanic crust and the theory of plate tectonics to explain the ages of crustal rocksGrade level(s) 9-12: Standard HS-ESS2-1 - Earth’s Systems - Develop a model to illustrate how Earth’s internal and surface processes operate at different spatial and temporal scales to form continental and ocean-floor features.Grade level(s) 9-12: Standard HS-ESS2-1 - Earth’s Systems - Develop a model to illustrate how Earth’s internal and surface processes operate at different spatial and temporal scales to form continental and ocean-floor features.Grade level(s) 9-12: Standard HS-ESS2-4 - Earth’s Systems - Use a model to describe how variations in the flow of energy into and out of Earth’s systems result in changes in climateGrade level(s) 9-12: Standard HS-ESS2-4 - Earth’s Systems - Use a model to describe how variations in the flow of energy into and out of Earth’s systems result in changes in climateGrade level(s) 9-12: Standard HS-ESS2-6 - Earth’s Systems - Develop a quantitative model to describe the cycling of carbon among the hydrosphere, atmosphere, geosphere, and biosphereGrade level(s) 9-12: Standard HS-ESS3-1 - Earth and Human Activity - Construct an explanation based on evidence for how the availability of natural resources, occurrence of natural hazards, and changes in climate have influenced human activityGrade level(s) 9-12: Standard HS-ESS3-4 - Earth and Human Activity - Evaluate or refine a technological solution that reduces impacts of human activities on natural systems.Grade level(s) 9-12: Standard HS-ESS3-5 - Earth and Human Activity - Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth’s systems.Grade level(s) 9-12: Standard HS-ESS3-5 - Earth and Human Activity - Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth’s systems.Grade level(s) 9-12: Standard HS-ESS3-6 - Earth and Human Activity - Use a computational representation to illustrate the relationships among Earth systems and how those relationships are being modified due to human activityGrade level(s) 9-12: Standard HS-ESS3-6 - Earth and Human Activity - Use a computational representation to illustrate the relationships among Earth systems and how those relationships are being modified due to human activityMost frequently used words:oceancurrentstripseaApproximate Flesch-Kincaid reading grade level: 10.0. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

Summary: Exploring with your class why Everest got tallerStorymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) K: Standard K-PS2-1 - Motion and Stability: Forces and Interactions - Plan and conduct an investigation to compare the effects of different strengths or different directions of pushes and pulls on the motion of an objectGrade level(s) K: Standard K-LS1-1 - From Molecules to Organisms: Structures and Processes - Use observations to describe patterns of what plants and animals (including humans) need to surviveGrade level(s) K: Standard K-ESS2-1 - Earth's Systems - Use and share observations of local weather conditions to describe patterns over timeGrade level(s) K: Standard K-ESS3-1 - Earth and Human Activity - Use a model to represent the relationship between the needs of different plants or animals (including humans) and the places they liveGrade level(s) 1: Standard 1-PS4-3 - Waves and their Applications in Technologies for Information Transfer - Plan and conduct an investigation to determine the effect of placing objects made with different materials in the path of a beam of lightGrade level(s) 1: Standard 1-ESS1-2 - Earth’s Place in the Universe - Make observations at different times of year to relate the amount of daylight to the time of yearGrade level(s) 2: Standard 2-PS1-1 - Matter and its Interactions - Plan and conduct an investigation to describe and classify different kinds of materials by their observable propertiesGrade level(s) 2: Standard 2-PS1-2 - Matter and its Interactions - Analyze data obtained from testing different materials to determine which materials have the properties that are best suited for an intended purposeGrade level(s) 2: Standard 2-PS1-4 - Matter and its Interactions - Construct an argument with evidence that some changes caused by heating or cooling can be reversed and some cannotGrade level(s) 2: Standard 2-LS4-1 - Biological Evolution: Unity and Diversity - Make observations of plants and animals to compare the diversity of life in different habitatsGrade level(s) 2: Standard 2-ESS2-1 - Earth’s Systems - Compare multiple solutions designed to slow or prevent wind or water from changing the shape of the landGrade level(s) 3: Standard 3-ESS2-2 - Earth’s Systems - Obtain and combine information to describe climates in different regions of the worldGrade level(s) 4: Standard 4-LS1-2 - From Molecules to Organisms: Structures and Processes - Use a model to describe that animals receive different types of information through their senses, process the information in their brain, and respond to the information in different waysGrade level(s) 4: Standard 4-ESS1-1 - Earth’s Place in the Universe - Identify evidence from patterns in rock formations and fossils in rock layers to support an explanation for changes in a landscape over timeGrade level(s) 4: Standard 4-ESS2-2 - Earth’s Systems - Analyze and interpret data from maps to describe patterns of Earth’s featuresGrade level(s) 5: Standard 5-ESS2-1 - Earth’s Systems - Develop a model using an example to describe ways the geosphere, biosphere, hydrosphere, and/or atmosphere interact.Grade level(s) 6-8: Standard MS-PS1-1 - Matter and Its Interactions - Develop models to describe the atomic composition of simple molecules and extended structuresGrade level(s) 6-8: Standard MS-PS3-2 - Energy - Develop a model to describe that when the arrangement of objects interacting at a distance changes, different amounts of potential energy are stored in the systemGrade level(s) 6-8: Standard MS-PS3-2 - Energy - Develop a model to describe that when the arrangement of objects interacting at a distance changes, different amounts of potential energy are stored in the systemGrade level(s) 6-8: Standard MS-PS3-4 - Energy - Plan an investigation to determine the relationships among the energy transferred, the type of matter, the mass, and the change in the average kinetic energy of the particles as measured by the temperature of the sampleGrade level(s) 6-8: Standard MS-LS1-1 - From Molecules to Organisms: Structures and Processes - Conduct an investigation to provide evidence that living things are made of cells; either one cell or many different numbers and types of cellsGrade level(s) 6-8: Standard MS-LS1-5 - From Molecules to Organisms: Structures and Processes - Construct a scientific explanation based on evidence for how environmental and genetic factors influence the growth of organismsGrade level(s) 6-8: Standard MS-LS2-2 - Ecosystems: Interactions, Energy, and Dynamics - Construct an explanation that predicts patterns of interactions among organisms across multiple ecosystemsGrade level(s) 6-8: Standard MS-LS3-1 - Heredity: Inheritance and Variation of Traits - Develop and use a model to describe why structural changes to genes (mutations) located on chromosomes may affect proteins and may result in harmful, beneficial, or neutral effects to the structure and function of the organismGrade level(s) 6-8: Standard MS-LS4-3 - Biological Evolution: Unity and Diversity - Analyze displays of pictorial data to compare patterns of similarities in the embryological development across multiple species to identify relationships not evident in the fully formed anatomy.Grade level(s) 6-8: Standard MS-ESS1-4 - Earth’s Place in the Universe - Construct a scientific explanation based on evidence from rock strata for how the geologic time scale is used to organize Earth’s 4.6-billion-year-old historyGrade level(s) 6-8: Standard MS-ESS2-2 - Earth’s Systems - Construct an explanation based on evidence for how geoscience processes have changed Earth’s surface at varying time and spatial scalesGrade level(s) 6-8: Standard MS-ESS2-3 - Earth’s Systems - Analyze and interpret data on the distribution of fossils and rocks, continental shapes, and seafloor structures to provide evidence of the past plate motions.Grade level(s) 6-8: Standard MS-ESS2-5 - Earth’s Systems - Collect data to provide evidence for how the motions and complex interactions of air masses result in changes in weather conditionsGrade level(s) 9-12: Standard HS-PS1-6 - Matter and Its Interactions - Refine the design of a chemical system by specifying a change in conditions that would produce increased amounts of products at equilibriumGrade level(s) 9-12: Standard HS-PS3-4 - Energy - Plan and conduct an investigation to provide evidence that the transfer of thermal energy when two components of different temperature are combined within a closed system results in a more uniform energy distribution among the components in the system (second law of thermodynamics).Grade level(s) 9-12: Standard HS-PS4-4 - Waves and Their Applications in Technologies for Information Transfer - Evaluate the validity and reliability of claims in published materials of the effects that different frequencies of electromagnetic radiation have when absorbed by matter.Grade level(s) 9-12: Standard HS-LS1-4 - From Molecules to Organisms: Structures and Processes - Use a model to illustrate the role of cellular division (mitosis) and differentiation in producing and maintaining complex organisms.Grade level(s) 9-12: Standard HS-LS2-1 - Ecosystems: Interactions, Energy, and Dynamics - Use mathematical and/or computational representations to support explanations of factors that affect carrying capacity of ecosystems at different scalesGrade level(s) 9-12: Standard HS-LS2-2 - Ecosystems: Interactions, Energy, and Dynamics - Use mathematical representations to support and revise explanations based on evidence about factors affecting biodiversity and populations in ecosystems of different scalesGrade level(s) 9-12: Standard HS-LS2-3 - Ecosystems: Interactions, Energy, and Dynamics - Construct and revise an explanation based on evidence for the cycling of matter and flow of energy in aerobic and anaerobic conditionsGrade level(s) 9-12: Standard HS-ESS1-3 - Earth’s Place in the Universe - Communicate scientific ideas about the way stars, over their life cycle, produce elementsGrade level(s) 9-12: Standard HS-ESS2-1 - Earth’s Systems - Develop a model to illustrate how Earth’s internal and surface processes operate at different spatial and temporal scales to form continental and ocean-floor features.Grade level(s) 9-12: Standard HS-ESS2-1 - Earth’s Systems - Develop a model to illustrate how Earth’s internal and surface processes operate at different spatial and temporal scales to form continental and ocean-floor features.Grade level(s) 9-12: Standard HS-ESS2-5 - Earth’s Systems - Plan and conduct an investigation of the properties of water and its effects on Earth materials and surface processesMost frequently used words:heightmeasuringeverestmountaindifferentApproximate Flesch-Kincaid reading grade level: 9.8. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.