The land classification shown is derived from in-field investigation and is only undertaken for project investigation purposes. These polygons represent the most accurate and up-to-date information regarding agriculture land conditions at those specific locations.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon’s digital map data collection. For more information: geomatics.help@yukon.ca

The Farmland Protection Policy Act, part of the 1981 Farm Bill, is intended to limit federal activities that contribute to the unnecessary conversion of farmland to other uses. The law applies to construction projects funded by the federal government such as highways, airports, and dams, and to the management of federal lands. As part of the implementation of this law, the Natural Resources Conservation Service identifies high quality agricultural soils as prime farmland, unique farmland, and land of statewide or local importance. Each category may contain one or more limitations such as Prime Farmland if Irrigated. For more information of farmland classification see the National Soil Survey Handbook.Dataset SummaryPhenomenon Mapped: FarmlandGeographic Extent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Mariana Islands, Republic of Palau, Republic of the Marshall Islands, Federated States of Micronesia, and American Samoa.Projection: Web Mercator Auxiliary SphereData Coordinate System: WKID 5070 USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WKID 3338 WGS 1984 Albers (Alaska), WKID 4326 WGS 1984 Decimal Degrees (Guam, Republic of the Marshall Islands, Northern Mariana Islands, Republic of Palau, Federated States of Micronesia, American Samoa, and Hawaii).Units: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerSource: Natural Resources Conservation ServiceUpdate Frequency: AnnualPublication Date: December 2024Data from the gNATSGO database was used to create the layer for the for the contiguous United States and Alaska. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Puerto Rico, the U.S. Virgin Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, Republic of the Marshall Islands, 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 farmland class is derived from the gSSURGO map unit table field Farm Class (farmlndcl).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 "farmland" 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 "farmland" 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.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.Data Dictionary'All areas are prime farmland' 1;'Farmland of local importance' 2;'Farmland of statewide importance' 3;'Farmland of statewide importance, if drained' 4;'Farmland of statewide importance, if drained and either protected from flooding or not frequently flooded during the growing season' 5;'Farmland of statewide importance, if irrigated' 6;'Farmland of statewide importance, if irrigated and drained' 7;'Farmland of statewide importance, if irrigated and either protected from flooding or not frequently flooded during the growing season' 8;'Farmland of statewide importance, if irrigated and reclaimed of excess salts and sodium' 9;'Farmland of statewide importance, if irrigated and the product of I (soil erodibility) x C (climate factor) does not exceed 60' 10;'Farmland of statewide importance, if protected from flooding or not frequently flooded during the growing season' 11;'Farmland of statewide importance, if warm enough' 12;'Farmland of statewide importance, if warm enough, and either drained or either protected from flooding or not frequently flooded during the growing season' 13;'Farmland of unique importance' 14;'Not prime farmland' 15;'Prime farmland if drained' 16;'Prime farmland if drained and either protected from flooding or not frequently flooded during the growing season' 17;'Prime farmland if irrigated' 18;'Prime farmland if irrigated and drained' 19;'Prime farmland if irrigated and either protected from flooding or not frequently flooded during the growing season' 20;'Prime farmland if irrigated and reclaimed of excess salts and sodium' 21;'Prime farmland if irrigated and the product of I (soil erodibility) x C (climate factor) does not exceed 60' 22;'Prime farmland if protected from flooding or not frequently flooded during the growing season' 23;'Prime farmland if subsoiled, completely removing the root inhibiting soil layer' 24;'Farmland of local importance, if irrigated' 25"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.

THE NYSERDA 2022 SOILS DATA IS TO BE USED FOR NYSERDA’S PROCUREMENT PURPOSES OR THE NY-SUN PROGRAM AND IS NOT INTENDED TO REPRESENT ACTUAL IN SITU SOIL CONDITIONS.

NYSERDA has launched the Renewable Energy Standard (RES) request for proposals, RESRFP22-1, to continue accelerating progress towards New York’s goal of generating 70 percent of its electricity from renewable sources by 2030. Through RESRFP22-1, NYSERDA seeks to procure approximately 4.5 million Tier 1 eligible Renewable Energy Certificates (RECs) from eligible facilities that enter commercial operation on or after January 1, 2015 and on or before November 30, 2024, unless extended to November 30, 2027.

In order to facilitate the protection of agricultural lands, developers participating in RESRFP22-1 or the NY-Sun program may be responsible for making an agricultural mitigation payment to a designated fund based on the extent to which the solar project’s facility area overlaps with an Agricultural District and New York’s highly productive agricultural soils, identified as Mineral Soil Groups (MSG) classifications 1 through 4 (MSG 1-4). This mitigation approach is designed to discourage solar projects from siting on MSG 1-4. Furthermore, this mitigation approach is designed to encourage retaining agricultural productivity on the project site. Instances where Proposers cannot avoid or minimize impacts on MSG 1-4 will result in a payment to a fund administered by NYSERDA. Disbursement of collected agricultural mitigation payment funds will be informed by consultation with the New York State Department of Agriculture and Markets (AGM) to support ongoing regional agricultural practices and/or soil conservation initiatives.

This dataset contains a combination of soils data from multiple sources to serve participants of NYSERDA’s Large-Scale Renewable and NY-Sun programs. The NYSERDA 2022 Soils Data was created by converting the 2022 New York State Agricultural Land Classification master list of soils maintained by AGM to a tabular form and providing a corresponding unique identifier for each listed soil that enables the user to link the soils to the Natural Resources Conservation Service (NRCS) SSURGO soils database, allowing for a geographical representation. When the NYSERDA 2022 Soils Data is joined with spatial data from the Natural Resources Conservation Service (NRCS) SSURGO soils database, the corresponding soil unit can be mapped in a geographic information system software. The latest version of the SSURGO database should be used to get the most accurate join. Data is updated yearly from both NRCS and from AGM, however, NYSERDA will not update this dataset and it will remain intact for future reference. NYSERDA intends on creating new soils datasets for future procurements on an annual basis.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

Abstract The Catchment Scale Land Use of Australia – Update December 2023 dataset is the national compilation of catchment scale land use data available for Australia (CLUM), as of December 2023. It replaces the Catchment Scale Land Use of Australia – Update December 2020. It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. The CLUM data shows a single dominant land use for a given area, based on the primary management objective of the land manager (as identified by state and territory agencies). Land use is classified according to the Australian Land Use and Management Classification version 8. It has been compiled from vector land use datasets collected as part of state and territory mapping programs and other authoritative sources, through the Australian Collaborative Land Use and Management Program. Catchment scale land use data was produced by combining land tenure and other types of land use information including, fine-scale satellite data, ancillary datasets, and information collected in the field. The date of mapping (2008 to 2023) and scale of mapping (1:5,000 to 1:250,000) vary, reflecting the source data, capture date and scale. Date and scale of mapping are provided in supporting datasets.

Currency Date modified: December 2023 Publication Date: June 2024 Modification frequency: As needed (approximately annual) Data Extent Coordinate reference: WGS84 / Mercator Auxiliary Sphere Spatial Extent North: -9.995 South: -44.005 East: 154.004 West: 112.505 Source information Data, Metadata, Maps and Interactive views are available from Catchment Scale Land Use of Australia - Update 2023 Catchment Scale Land Use of Australia - Update 2023 – Descriptive metadata The data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license. Lineage statement This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). 2023 updates include more current data and/or reclassification of existing data. The following areas have updated data since the December 2020 version:

New South Wales (2017 v1.5 from v1.2). Northern Territory (2022 from 2020). Tasmania (2021 from 2019). Victoria (2021 from 2017). Data were also added from the Great Barrier Reef Natural Resource Management (NRM) regions in Queensland (2021 from a variety of dates 2009 to 2017). the Australian Tree Crops. Australian Protected Cropping Structures and Queensland Soybean Crops maps as downloaded on 30 November 2023. The capital city of Adelaide was updated using 2021 mesh block information from the Australian Bureau of Statistics. Minor reclassifications were made for Western Australia and mining area within mining tenements more accurately delineated in South Australia.

Links to land use mapping datasets and metadata are available at the ACLUMP data download page at agriculture.gov.au. State and territory vector catchment scale land use data were produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field, as outlined in 'Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition' (ABARES 2011). The Northern Territory, Queensland, South Australia, Tasmania, Victoria and Western Australia were mapped to version 8 of the ALUM classification (‘The Australian Land Use and Management Classification Version 8’, ABARES 2016). The Australian Capital Territory was mapped to version 7 of the ALUM classification and converted to version 8 using a look-up table based on Appendix 1 of ABARES (2016). Purpose for which the material was obtained: This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). Do not use this data to:

Derive national statistics. The Land use of Australia data series should be used for this purpose. Calculate land use change. The Land use of Australia data series should be used for this purpose.

It is not possible to calculate land use change statistics between annual CLUM national compilations as not all regions are updated each year; land use mapping methodologies, precision, accuracy and source data and satellite imagery have improved over the years; and the land use classification has changed over time. It is only possible to calculate change when earlier land use datasets have been revised and corrected to ensure that changes detected are real change and not an artefact of the mapping process. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in October 2024 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster was created with RGB fields as a colour map with Geoprocessing tools in ArcPro. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in February 2025 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster dataset was created with RGB fields as a colour map with Geoprocessing tools in ArcPro, and the raster dataset was re-projected from 1994 Australia Albers to WGS 1984 Web Mercator (Auxiliary Sphere). Data dictionary

Field name DField description Code values

OID Internal feature number that uniquely identifies each row Integer

Service Pixel value (Date) The year for which land use was mapped in the vector data provided by state and territory agencies or others, Date Range: 2008 to 2023 Integer

Count Count of the number of raster cells in each class of VALUE Integer

Label Reflecting the Date of the source data ranges from 2008 to 2023 Text

Contact Department of Agriculture, Fisheries and Forestry (ABARES), info.ABARES@aff.gov.au

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.

Provisional Agricultural Land Classification Grade. Agricultural land classified into five grades. Grade one is best quality and grade five is poorest quality. A number of consistent criteria used for assessment which include climate (temperature, rainfall, aspect, exposure, frost risk), site (gradient, micro-relief, flood risk) and soil (depth, structure, texture, chemicals, stoniness) for England only. Digitised from the published 1:250,000 map which was in turn compiled from the 1 inch to the mile maps.More information about the Agricultural Land Classification can be found at the following links:http://webarchive.nationalarchives.gov.uk/20130402200910/http://archive.defra.gov.uk/foodfarm/landmanage/land-use/documents/alc-guidelines-1988.pdfhttp://publications.naturalengland.org.uk/publication/35012.Full metadata can be viewed on data.gov.uk.

Use this country model layer when performing analysis within a single country. This layer displays a single global land cover map that is modeled by country for the year 2050 at a pixel resolution of 300m. ESA CCI land cover from the years 2010 and 2018 were used to create these predictions. Variable mapped: Projected land cover in 2050. Data Projection: Cylindrical Equal Area Mosaic Projection: Cylindrical Equal Area Extent: Global Cell Size: 300m Source Type: Thematic Visible Scale: 1:50,000 and smaller Source: Clark University Publication date: April 2021What you can do with this layer? This layer may be added to online maps and compared with the ESA CCI Land Cover from any year from 1992 to 2018. To do this, add Global Land Cover 1992-2018 to your map and choose the processing template (image display) from that layer called “Simplified Renderer.” This layer can also be used in analysis in ecological planning to find specific areas that may need to be set aside before they are converted to human use. Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World:There are three scales (country, regional, and world) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between countries, use the country level. If mapping larger patterns, use the global or regional extent (depending on your area of interest). Land Cover 2050 WorldLand Cover 2050 RegionalLand Cover 2050 CountryLand Cover Vulnerability Change 2050 WorldLand Cover Vulnerability Change 2050 RegionalLand Cover Vulnerability Change 2050 CountryWhat these layers model (and what they don’t model) The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many. The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use. Quantitative Variables used to create Models Biomass Crop Suitability Distance to Airports Distance to Cropland 2010 Distance to Primary Roads Distance to Railroads Distance to Secondary Roads Distance to Settled Areas Distance to Urban 2010 Elevation GDP Human Influence Index Population Density Precipitation Regions Slope Temperature Qualitative Variables used to create Models Biomes Ecoregions Irrigated Crops Protected Areas Provinces Rainfed Crops Soil Classification Soil Depth Soil Drainage Soil pH Soil Texture Were small countries modeled?Clark University modeled some small countries that had a few transitions. Only five countries were modeled with this procedure: Bhutan, North Macedonia, Palau, Singapore and Vanuatu.As a rule of thumb, the MLP neural network in the Land Change Modeler requires at least 100 pixels of change for model calibration. Several countries experienced less than 100 pixels of change between 2010 & 2018 and therefore required an alternate modeling methodology. These countries are Bhutan, North Macedonia, Palau, Singapore and Vanuatu. To overcome the lack of samples, these select countries were resampled from 300 meters to 150 meters, effectively multiplying the number of pixels by four. As a result, we were able to empirically model countries which originally had as few as 25 pixels of change. Once a selected country was resampled to 150 meter resolution, three transition potential images were calibrated and averaged to produce one final transition potential image per transition. Clark Labs chose to create averaged transition potential images to limit artifacts of model overfitting. Though each model contained at least 100 samples of "change", this is still relatively little for a neural network-based model and could lead to anomalous outcomes. The averaged transition potentials were used to extrapolate change and produce a final hard prediction and risk map of natural land cover conversion to Cropland and Artificial Surfaces in 2050. 39 Small Countries Not ModeledThere were 39 countries that were not modeled because the transitions, if any, from natural to anthropogenic were very small. In this case the land cover for 2050 for these countries are the same as the 2018 maps and their vulnerability was given a value of 0. Here were the countries not modeled:AndorraAntigua and BarbudaBarbadosCape VerdeComorosCook IslandsDjiboutiDominicaFaroe IslandsFrench GuyanaFrench PolynesiaGibraltarGrenadaGuamGuyanaIcelandJan MayenKiribatiLiechtensteinLuxembourgMaldivesMaltaMarshall IslandsMicronesia, Federated States ofMoldovaMonacoNauruSaint Kitts and NevisSaint LuciaSaint Vincent and the GrenadinesSamoaSan MarinoSeychellesSurinameSvalbardThe BahamasTongaTuvaluVatican CityIndex to land cover values in this dataset: The Clark University Land Cover 2050 projections display a ten-class land cover generalized from ESA Climate Change Initiative Land Cover. 1 Mostly Cropland 2 Grassland, Scrub, or Shrub 3 Mostly Deciduous Forest 4 Mostly Needleleaf/Evergreen Forest 5 Sparse Vegetation 6 Bare Area 7 Swampy or Often Flooded Vegetation 8 Artificial Surface or Urban Area 9 Surface Water 10 Permanent Snow and Ice

Abstract The Catchment Scale Land Use of Australia – Update December 2023 dataset is the national compilation of catchment scale land use data available for Australia (CLUM), as of December 2023. It replaces the Catchment Scale Land Use of Australia – Update December 2020. It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. The CLUM data shows a single dominant land use for a given area, based on the primary management objective of the land manager (as identified by state and territory agencies). Land use is classified according to the Australian Land Use and Management Classification version 8. It has been compiled from vector land use datasets collected as part of state and territory mapping programs and other authoritative sources, through the Australian Collaborative Land Use and Management Program. Catchment scale land use data was produced by combining land tenure and other types of land use information including, fine-scale satellite data, ancillary datasets, and information collected in the field. The date of mapping (2008 to 2023) and scale of mapping (1:5,000 to 1:250,000) vary, reflecting the source data, capture date and scale. Date and scale of mapping are provided in supporting datasets.

Currency Date modified: December 2023 Date Published: June 2024 Modification frequency: As needed (approximately annual) Data Extent Coordinate reference: WGS84 / Mercator Auxiliary Sphere Spatial Extent North: -9.995 South: -44.005 East: 154.004 West: 112.505 Source information Data, Metadata, Maps and Interactive views are available from Catchment Scale Land Use of Australia - Update 2023 Catchment Scale Land Use of Australia - Update 2023 – Descriptive metadata The data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license. Lineage Statement This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). 2023 updates include more current data and/or reclassification of existing data. The following areas have updated data since the December 2020 version:

New South Wales (2017 v1.5 from v1.2). Northern Territory (2022 from 2020). Tasmania (2021 from 2019). Victoria (2021 from 2017). Data were also added from the Great Barrier Reef Natural Resource Management (NRM) regions in Queensland (2021 from a variety of dates 2009 to 2017). the Australian Tree Crops. Australian Protected Cropping Structures and Queensland Soybean Crops maps as downloaded on 30 November 2023. The capital city of Adelaide was updated using 2021 mesh block information from the Australian Bureau of Statistics. Minor reclassifications were made for Western Australia and mining area within mining tenements more accurately delineated in South Australia.

Links to land use mapping datasets and metadata are available at the ACLUMP data download page at agriculture.gov.au. State and territory vector catchment scale land use data were produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field, as outlined in 'Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition' (ABARES 2011). The Northern Territory, Queensland, South Australia, Tasmania, Victoria and Western Australia were mapped to version 8 of the ALUM classification (‘The Australian Land Use and Management Classification Version 8’, ABARES 2016). The Australian Capital Territory was mapped to version 7 of the ALUM classification and converted to version 8 using a look-up table based on Appendix 1 of ABARES (2016). Purpose for which the material was obtained: This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). Do not use this data to:

Derive national statistics. The Land use of Australia data series should be used for this purpose. Calculate land use change. The Land use of Australia data series should be used for this purpose.

It is not possible to calculate land use change statistics between annual CLUM national compilations as not all regions are updated each year; land use mapping methodologies, precision, accuracy and source data and satellite imagery have improved over the years; and the land use classification has changed over time. It is only possible to calculate change when earlier land use datasets have been revised and corrected to ensure that changes detected are real change and not an artefact of the mapping process. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in October 2024 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster was created with RGB fields as a colour map with Geoprocessing tools in ArcPro. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in February 2025 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster dataset was created with RGB fields as a colour map with Geoprocessing tools in ArcPro, and the raster dataset was re-projected from 1994 Australia Albers to WGS 1984 Web Mercator (Auxiliary Sphere). Data dictionary

Attribute name Description

OID Internal feature number that uniquely identifies each row.

Service Pixel value (Scale) The scale at which land use was mapped in the vector catchment scale land use data provided by state and territory agencies or others:1:5,000, 1:10,000, 1:20,000, 1:25,000, 1:50,000, 1:100,000 or 1:250,000

Count Count of the number of raster cells in each class of VALUE.

Label Reflecting the scale of the source data ranges from 1:5,000 to 1:250,000

Contact Department of Agriculture, Fisheries and Forestry (ABARES), info.ABARES@aff.gov.au

This map is a compilation of seven published Soil and Land Resource products which contain baseline natural resource information for the:

• Hawkesbury-Nepean catchment
• Liverpool Plains catchment
• Merriwa Plateau
• Moree Plains
• Murray catchment
• Australian Capital Territory
• Hunter Region

These products were undertaken to enhance knowledge of soils, landscapes and physical constraints to land use in the urban and rural environment. The information will assist in informed decision making, planning and environmental modelling throughout the catchments. The Soil and Land Resource mapping for the Merriwa Plateau and Moree Plains were funded to especially improve existing soil landscape information so more accurate Land and Soil Capability (LSC) and Soil Fertility information would be available to upgrade future Biophysical Strategic Agricultural Land (BSAL) mapping under NSW Strategic Regional Land Use Policy (SRLUP).

One thousand, one hundred and seventeen map units have been described in this combined Soil and Land Resource product. Each soil landscape unit is an inventory of soil and landscape information with relatively uniform land management requirements, allowing major soil and landscape qualities and constraints to be identified. Soils are described using the Australian Soil Classification and the Great Soil Groups systems.

Online Maps: Part of this area is also covered by other soil mapping products, see the soil map index in eSPADE. eSPADE contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area.

Reference: Office of Environment and Heritage, 2018, Soil and Land Resources of Central and Eastern NSW, Version 3, NSW Office of Environment and Heritage, Sydney.

The Sacramento-San Joaquin Delta Reform Act of 2009 established the Delta Stewardship Council (DSC) to achieve more effective governance while providing for the sustainable management of the Delta ecosystem and a more reliable water supply, using an adaptive management framework. Vegetation and land use are mapped for the 737,621 acres constituting the Legal Delta portion of the Sacramento and San Joaquin River Delta area. The current effort produced a digital map covering 737,621 acres considered to be the Legal Delta Area. 2016 National Agricultural Imagery Program (NAIP) 1-meter resolution imagery was used to delineate line work and attribute polygons. The 2019 map is a re-map of the 2007 effort. This map retained the line work and attributes of the 2007 mapping when static and was amended in areas where change occurred. Change detection was done comparing 723,426 acres, which were identical in the 2007 (2005 base imagery) and 2019 (2016 base imagery) efforts. GIC utilized the key produced for the 2007 mapping effort, in conjunction with the 2009 Central Valley key, as well as the CNPS membership rules online to determine classification levels and vegetation communities. Vegetation mapping is to alliance level when possible, otherwise it is left at group level (based on the National Vegetation Classification Standard, see http://biology.usgs.gov/npsveg/nvcs.html); land use is mapped to Anderson Level 2 classification (see https://pubs.usgs.gov/pp/0964/report.pdf). The map classification is based on a vegetation classification derived from field data collected in summer and fall of 2005 produced by the Vegetation Classification and Mapping Program (VegCAMP) of the Department of Fish and Wildlife. Membership rules for each alliance can be found at http://vegetation.cnps.org/. 2016 National Agricultural Inventory Program (NAIP) one meter orthoimagery was the baseline imagery used. Google Earth imagery was used as supplemental imagery. Natural vegetation comprises approximately 17% of the Delta study area, 65% is agriculture and pasture, 10% is urban/other and 8% is open water. The minimum mapping unit was 250 acres (100 ha). Link to download report: https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=174866.

This map is a compilation of seven published Soil and Land Resource products which contain baseline natural resource information for the: Hawkesbury-Nepean catchment Liverpool Plains catchment Merriwa …Show full descriptionThis map is a compilation of seven published Soil and Land Resource products which contain baseline natural resource information for the: Hawkesbury-Nepean catchment Liverpool Plains catchment Merriwa Plateau Moree Plains Murray catchment Australian Capital Territory Hunter Region These products were undertaken to enhance knowledge of soils, landscapes and physical constraints to land use in the urban and rural environment. The information will assist in informed decision making, planning and environmental modelling throughout the catchments. The Soil and Land Resource mapping for the Merriwa Plateau and Moree Plains were funded to especially improve existing soil landscape information so more accurate Land and Soil Capability (LSC) and Soil Fertility information would be available to upgrade future Biophysical Strategic Agricultural Land (BSAL) mapping under NSW Strategic Regional Land Use Policy (SRLUP). One thousand, one hundred and seventeen map units have been described in this combined Soil and Land Resource product. Each soil landscape unit is an inventory of soil and landscape information with relatively uniform land management requirements, allowing major soil and landscape qualities and constraints to be identified. Soils are described using the Australian Soil Classification and the Great Soil Groups systems. Online Maps: Part of this area is also covered by other soil mapping products, see the soil map index in eSPADE. eSPADE contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area. Reference: Office of Environment and Heritage, 2018, Soil and Land Resources of Central and Eastern NSW, NSW Office of Environment and Heritage, Sydney.

The maps show the soil cover of the Czech Republic. They express the typological affiliation of the soil in the "Taxonomic classification system of soils of the Czech Republic" (Němeček et al., 2011), or the version for forest soils (Vokoun et al., 2002), i.e. soil type, subtype, soil variety, or subvariety. The data for the selected map sheets also contain data on the soil parent material in a classification based on the legend of the Geological Map of the Czech Republic 1:50,000, supplemented by classification codes (Schuler et al,. 2013). This soil map on a scale of 1:50,000 is the most detailed soil map so far, which maps both agricultural and forest land together in the area of the entire territory of the Czech Republic (in process), in the same and up-to-date soil classification system. In the GIS environment, the maps are processed after the map sheets of the ZM50 division, so that they create a continuous thematic layer of the soil-typology map.

The Yukon Geological Survey (YGS) has compiled over 195 surficial geology maps into a standardized GIS format, providing approximately 80% coverage of the territory. The maps range in scales from 1:250,000 to 1:10,000 with spatial overlap between scales. The original maps were produced by various agencies, including the Geological Survey of Canada, YGS, Yukon Government, universities, and the City of Whitehorse. All original feature descriptions have been preserved and also converted to standardized values using the Yukon terrain classification system. The compilation includes 4 GIS datasets and supporting documents available for download via YGS integrated data system (YGSIDS) or GeoYukon. A .lyr file is provided to symbolize feature classes and differentiate overlapping maps at different scales. Additionally, there is a surficial geology map index. The polygon attributes captured include surficial material, texture, age, surface expression, and geomorphological processes. Line features include geological contacts, glacial limits, glacial landforms (cirques, arêtes, eskers, meltwater channels, moraines), and non-glacial landforms (faults, lineaments, landslides, escarpments). Point features include field station, fossil and sample locations, glacial landforms (erratics, kames, kettles, drumlins, flutings), permafrost features (pingos, palsas, patterned ground, thermokarst depressions), and other non-glacial landforms (landslides, tors). The map index provides information on each map publication such as author, map title, map scale, publisher. These data are valuable for land-use applications in the territory, including: mineral and placer exploration, geotechnical engineering, infrastructure planning, granular resource assessments, permafrost modeling, agricultural assessments, forest management, and biophysical or ecological land classification. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

The Yukon Geological Survey (YGS) has compiled over 195 surficial geology maps into a standardized GIS format, providing approximately 80% coverage of the territory. The maps range in scales from 1:250,000 to 1:10,000 with spatial overlap between scales. The original maps were produced by various agencies, including the Geological Survey of Canada, YGS, Yukon Government, universities, and the City of Whitehorse. All original feature descriptions have been preserved and also converted to standardized values using the Yukon terrain classification system. The compilation includes 4 GIS datasets and supporting documents available for download via YGS integrated data system (YGSIDS) or GeoYukon. A .lyr file is provided to symbolize feature classes and differentiate overlapping maps at different scales. Additionally, there is a surficial geology map index. The polygon attributes captured include surficial material, texture, age, surface expression, and geomorphological processes. Line features include geological contacts, glacial limits, glacial landforms (cirques, arêtes, eskers, meltwater channels, moraines), and non-glacial landforms (faults, lineaments, landslides, escarpments). Point features include field station, fossil and sample locations, glacial landforms (erratics, kames, kettles, drumlins, flutings), permafrost features (pingos, palsas, patterned ground, thermokarst depressions), and other non-glacial landforms (landslides, tors). The map index provides information on each map publication such as author, map title, map scale, publisher. These data are valuable for land-use applications in the territory, including: mineral and placer exploration, geotechnical engineering, infrastructure planning, granular resource assessments, permafrost modeling, agricultural assessments, forest management, and biophysical or ecological land classification. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

AbstractCatchment Scale Land Use of Australia (CLUM), depicted as 19 simplified land use classes based on the simplified classes of the Australian Land Use and Management (ALUM) Classification version 8.The classes are Nature conservation, Managed resource protection, Other minimal use, Grazing native vegetation, Production native forests, Grazing modified pastures, Plantation forests (commercial and other), Dryland cropping, Dryland horticulture, Land in transition, Irrigated pastures, Irrigated cropping, Irrigated horticulture, Intensive horticulture and animal production, Rural residential and farm infrastructure, Urban residential, Other intensive uses, Mining and waste, and Water.The Catchment Scale Land Use of Australia – Update December 2023 version 2 dataset is the national compilation of catchment scale land use data available for Australia, as at December 2023. It replaces the Catchment Scale Land Use of Australia – Update December 2020.It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. The CLUM data shows a single dominant land use for a given area, based on the primary management objective of the land manager (as identified by state and territory agencies).Land use is classified according to the Australian Land Use and Management Classification version 8. It has been compiled from vector land use datasets collected as part of state and territory mapping programs and other authoritative sources, through the Australian Collaborative Land Use and Management Program. Catchment scale land use data was produced by combining land tenure and other types of land use information including, fine-scale satellite data, ancillary datasets, and information collected in the field.The date of mapping (2008 to 2023) and scale of mapping (1:5,000 to 1:250,000) vary, reflecting the source data, capture date and scale. Date and scale of mapping are provided in supporting datasets.CurrencyDate modified: June 2024Modification frequency: As requiredData extentSpatial extentNorth: -8.03°South: -45.5°East: 161.5°West: 105.7°Source informationData, Metadata, Maps and Interactive views are available from Catchment Scale Land Use of Australia - Update 2023Catchment Scale Land Use of Australia - Update 2023 – Descriptive metadataThe data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license.Lineage statementABARES has produced this raster dataset from vector catchment scale land use data provided by state and territory agencies, as follows:Catchment Scale Land Use Mapping for the Australian Capital Territory 20122017 NSW Land Use v1.5Land Use Mapping Project of the Northern Territory, 2016 – 2022 (LUMP)Land use mapping – 2021 – Great Barrier Reef NRM regionsLand use mapping – 1999 to Current – Queensland (June 2019)[South Australia] Land Use (ACLUMP) (2017)Tasmanian Land Use 2022Victorian Land Use Information System [VLUIS] 2021-22Catchment Scale Land Use Mapping for Western Australia 2018Australian Tree Crops, Australian Protected Cropping Structures and Queensland Soybean Crops maps (as at 30 November 2023)Applied Agricultural Remote Sensing Centre (AARSC), University of New England.Links to land use mapping datasets and metadata are available at the ACLUMP data download page at agriculture.gov.au.State and territory vector catchment scale land use data were produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field, as outlined in 'Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition' (ABARES 2011). The Northern Territory, Queensland, South Australia, Tasmania, Victoria and Western Australia were mapped to version 8 of the ALUM classification (‘The Australian Land Use and Management Classification Version 8’, ABARES 2016).The Australian Capital Territory was mapped to version 7 of the ALUM classification and converted to version 8 using a look-up table based on Appendix 1 of ABARES (2016).The following agricultural (excluding intensive uses) classes were included from the Queensland Great Barrier Reef NRM Regions 2021 modified ALUM classification schema dataset:2.2.0 Grazing native vegetation3.2.0 Grazing modified pastures3.3.0 Cropping3.3.5 Sugar3.4.0 Perennial horticulture3.4.1 Tree fruits3.5.0 Seasonal horticulture3.6.0 Land in transition4.2.0 Grazing irrigated modified pastures4.3.0 Irrigated cropping4.3.5 Irrigated sugar4.4.0 Irrigated perennial horticulture4.4.1 Irrigated tree fruits4.5.0 Irrigated seasonal horticulture4.6.0 Irrigated land in transitionFixes to known issues include:In Western Australia, ALUM classes 4.0.0 Production from Irrigated Agriculture and Plantations, 5.0.0 Intensive Uses and 6.0.0 Water have been attributed to secondary level by visual interpretation using satellite data.In South Australia, through consultation with the South Australian Department of Environment and Water, the mining area (ALUM class 5.8.0 Mining) within mining tenements is more accurately delineated. The area within mining tenements that is not used for mining is now attributed as grazing of native vegetation (ALUM class 2.1.0) within pastoral areas and residual native cover (ALUM class 1.3.3) outside of pastoral areas.NODATA voids in Adelaide, South Australia were filled with data from mesh block land use attributes (Australian Bureau of Statistics 2021) according to Table 8. All other NODATA voids were filled using the ESRI ArcGIS focal statistics command.For the purposes of web viewing, the data was reprojected to EPSG:3857 - Web Mercator.Land use classificationThe Australian Land Use and Management (ALUM) Classification version 8 is a three-tiered hierarchical structure. There are five primary classes, identified in order of increasing levels of intervention or potential impact on the natural landscape. Water is included separately as a sixth primary class. Primary and secondary levels relate to the principal land use. Tertiary classes may include additional information on commodity groups, specific commodities, land management practices or vegetation information. The primary, secondary and tertiary codes work together to provide increasing levels of detail about the land use. Land may be subject to concurrent uses. For example, while the main management objective of a multiple-use production forest may be timber production, it may also provide conservation, recreation, grazing and water catchment land uses. In these cases, production forestry is commonly identified in the ALUM code as the prime land use.Table 1: Simplified land use classification symbology as RGB and hexadecimal colour valuesVALUESIMPNSIMPRedGreenBlueHex110; 111; 112; 113; 114; 115; 116; 1171Nature conservation150102204#9666CC120; 121; 122; 123; 124; 1252Managed resource protection201190255#C9BEFF130; 131; 132; 133; 1343Other minimal use222135221#DE87DD2104Grazing native vegetation255255229#FFFFE5220; 221; 2225Production native forests4113768#298944310; 311; 312; 313; 314; 410; 411; 412; 413; 4146Plantation forests173255181#ADFFB5320; 321; 322; 323; 324; 3257Grazing modified pastures255211127#FFD37F330; 331; 332; 333; 334; 335; 336; 337; 3388Dryland cropping2552550#FFFF00340; 341; 342; 343; 344; 345; 346; 347; 348; 349; 350; 351; 352; 3539Dryland horticulture171135120#AB8778360; 361; 362; 363; 364; 365; 460; 461; 462; 463; 464; 46510Land in transition000#000000420; 421; 422; 423; 42411Irrigated pastures2551700#FFAA00430; 431; 432; 433; 434; 435; 436; 437; 438; 43912Irrigated cropping20118484#C9B854440; 441; 442; 443; 444; 445; 446; 447; 448; 449; 450; 451; 452; 453; 45413Irrigated horticulture1568446#9C542E510; 511; 512; 513; 514; 515; 520; 521; 522; 523; 524; 525; 526; 527; 52814Intensive horticulture and animal production255201190#FFC9BE542; 543; 544; 54515Rural residential and farm infrastructure178178178#B2B2B2540; 54116Urban residential25500#FF0000530; 531; 532; 533; 534; 535; 536; 537; 538; 550; 551; 552; 553; 554; 555; 560; 561; 562; 563; 564; 565; 566; 567; 570; 571; 572; 573; 574; 57517Other intensive uses15500#9B0000580; 581; 582; 583; 584; 590; 591; 592; 593; 594; 59518Mining and waste71130143#47828F610; 611; 612; 613; 614; 620; 621; 622; 623; 630; 631; 632; 633; 640; 641; 642; 643; 650; 651; 652; 653; 654; 660; 661; 662; 66319Water00255#0000FF Note: Codes refer to the Australian Land Use and Management (ALUM) Classification, version 8.SIMPN 0 = No data is not present in Catchment Scale land Use of Australia 2023Data dictionaryAttribute nameDescriptionOIDInternal feature number that uniquely identifies each row.VALUEALUM code as a three digit integer. First digit is primary code, second digit is secondary code, and third digit is tertiary code.COUNTCount of the number of raster cells in each class of VALUE.LU_CODEV8ALUM code as a string.LU_V8NALUM code as a three digit integer. First digit is primary code, second digit is secondary code, and third digit is tertiary code.TERTV8ALUM tertiary code and description as a string.SECV8ALUM secondary code and description as a string.PRIMV8ALUM primary code and description as a string.SIMPNCode for simplified land use classification.SIMPDescription of the simplified land use classification.AGINDDescription of agricultural industries.Red, Green, BlueRGB values for classification colours ContactDepartment of Agriculture, Fisheries and Forestry (ABARES), info.ABARES@aff.gov.au

This digital soil landscape product contains natural resource mapping for the Merriwa. The Merriwa Plateau is located in the upper Hunter catchment including hills of the Southern Liverpool Ranges; grading to gently sloped plateau around Merriwa. The project was funded by the National Partnership Agreement to provide improved soil and landscape information for this highly productive agricultural area. It has enabled more accurate and better quality Land and Soil Capability and Soil Fertility information to be available for future updates of Biophysical Strategic Agricultural Land (BSAL) mapping under the NSW Strategic Regional Land Use Policy (SRLUP). This resource information will also assist other decision making, planning and environmental modelling throughout the catchment.

Forty soil landscape map units have been described for the Merriwa Plateau. Each unit is an inventory of soil and landscape information with relatively uniform land management requirements, allowing major soil and landscape qualities and constraints to be identified. Soils are described using the Australian Soil Classification and the Great Soil Groups systems.

Related Datasets: The dataset area is also covered by the mapping of the Soil landscape 1:100 000 and 1:250 000 mapping series for the mapsheets of Dubbo, Singleton, Murrurundi and Blackville. Part of this area is also covered by the mapping of Hydrogeological landscapes of NSW.

Online Maps: This and related datasets can be viewed using eSPADE (NSW’s soil spatial viewer), which contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area.

Reference: Office of Environment and Heritage, 2014, Soil and Land Resources of the Merriwa Plateau, NSW Office of Environment and Heritage, Sydney.

AEZ classification by climate, soil, terrain and land cover (57 classes) at about 1 km resolution at the equator, using different climate data source and based on different Representative Concentration Pathways (RCPs) according to the time period as follows: - climate data source CRUTS32 based on historical data for the time period 1981-2010; - climate data source ENSEMBLE based on the Representative Concentration Pathway RCP8.5 for time periods 2041-2070 and 2071-2100.

The AEZ classification by climate, soil, terrain and land cover dataset is part of the GAEZ v4 Theme 1 Land and Water Resources, Agro-Ecological Zones sub-theme.

The agro-ecological zones classification provides a characterization of bio-physical resources relevant to agricultural production systems. AEZ definitions and map classes follow a rigorous methodology and an explicit set of principles. The inventory combines spatial layers of thermal and moisture regimes with broad categories of soil/terrain qualities. It also indicates locations of areas with irrigated soils and shows land with severely limiting bio-physical constraints including very cold and very dry (desert) areas as well as areas with very steep terrain or very poor soil/terrain conditions.

For further details, please refer to the GAEZ v4 Model Documentation.

Data publication: 2021-05-01

Supplemental Information:

The GAEZ v4 Land and Water Resources theme provides a framework for establishing a spatial inventory of land resources. It includes selected layers organized in several sub-themes of (1) Agro-ecological Zones, (2) Land Cover, (3) Soil Resources, (4) Soil Suitability, (5) Terrain Resources, (6) Exclusion Areas, (7) Water Resources, and (8) Selected Socio-economic Data. The land resources inventory provide the spatial characteristics required for land productivity assessments concerning location-speciďŹ c agro-ecological conditions. It contains spatial layers of climate, land cover, soil, elevation and terrain slopes, protected areas and areas of high biodiversity value, administrative units, watersheds, population and livestock distribution. For further details, please refer to the GAEZ v4 Model Documentation.

Contact points:

Resource Contact: Fischer Gunther

Resource Contact: UNFAO - NSL Geospatial Unit

Metadata Contact: GAEZ

Resource constraints:

GAEZ v4 Disclaimer at https://gaez.fao.org/pages/disclaimer

Online resources:

GAEZ v4 Model Documentation

GAEZ v4 Data Portal

Download data: AEZ classification by climate/soil/terrain/LC (57 classes) for the time period 1981-2010 using climate data source CRUTS32 based on historical data

Data for download: AEZ classification by climate/soil/terrain/LC (57 classes) for the time period 2041-2070 using climate data source ENSEMBLE based on RCP8.5

Data for download: AEZ classification by climate/soil/terrain/LC (57 classes) for the time period 2071-2100 using climate data source ENSEMBLE based on RCP8.5

Ecosystem Science and Visualization : Yellowstone National Park provides access to data other products arising from our wildlife ecological and landscape research in Yellowstone National Park.

Research will involve development of remote sensing products (land cover, phenology, snowpack, geothermals), simulation models (snowpack, phenology, animal behavior), a data bundle and approach to integration of interdisciplinary data, and continued development of the Tarsier software framework for dynamic, interactive systems integration and visualization of the Earth System. The result will be a unification of data with diverse interdisciplinary field data on wildlife tracking, snowpack, geothermals, and other system elements – thus leveraging products toward new knowledge.

Application products will include dynamic, interactive computer visualization systems for decision support, placed in public kiosks and deployed in management forums. Prototyping to date has achieved unprecedented integration of remote sensing, field, and modeling data sets into a unified virtual-reality ecosystem representation. Product users have been identified from four groups: Park visitors, Park managers, Park scientists, and students.

Education needs will be addressed by using the visualization system as a unique teaching tool. The visualizations will provide as essential product to spark interest, train students, and teach marketable skills in earth system science.

[Summary provided by NASA.]

Soil-landscape mapping covering Western Australia at the best available scale (Version 05.02). It is a compilation of various surveys at different scales varying between 1:20,000 and 1:3,000,000. Mapping conforms to a nested hierarchy established to deal with the varying levels of information resulting from the variety of scales in mapping. For further information refer to Department of Agriculture Resource Management Technical Reports RMTR No. 280 and RMTR No. 313. Land capability and land quality attribution is included, refer to Department of Agriculture Resource Management Technical Report No. 298 for a description of the methodology employed.

THE NYSERDA 2024 SOILS DATA IS TO BE USED FOR NYSERDA’S RENEWABLE ENERGY STANDARD (RES) REQUEST FOR PROPOSAL (RFP) ISSUED AFTER THE PUBLICATION OF THIS DATA OR THE NY-SUN PROGRAM AND IS NOT INTENDED TO REPRESENT ACTUAL IN SITU SOIL CONDITIONS.

In order to facilitate the protection of agricultural lands, developers participating in RESRFPs or the NY-Sun program may be responsible for making an agricultural mitigation payment to a designated fund based on the extent to which the solar project’s facility area overlaps with an Agricultural District and New York’s highly productive agricultural soils, identified as Mineral Soil Groups (MSG) classifications 1 through 4 (MSG 1-4). This mitigation approach is designed to discourage solar projects from siting on MSG 1-4. Furthermore, this mitigation approach is designed to encourage retaining agricultural productivity on the project site. Instances where Proposers cannot avoid or minimize impacts on MSG 1-4 will result in a payment to a fund administered by NYSERDA. Disbursement of collected agricultural mitigation payment funds will be informed by consultation with the New York State Department of Agriculture and Markets (AGM) to support ongoing regional agricultural practices and/or soil conservation initiatives.

This dataset contains a combination of soils data from multiple sources to serve participants of NYSERDA’s Large-Scale Renewable and NY-Sun programs. The NYSERDA 2024 Soils Data was created by converting the 2024 New York State Agricultural Land Classification master list of soils maintained by AGM to a tabular form and providing a corresponding unique identifier for each listed soil that enables the user to link the soils to the Natural Resources Conservation Service (NRCS) SSURGO soils database, allowing for a geographical representation. When the NYSERDA 2024 Soils Data is joined with spatial data from the Natural Resources Conservation Service (NRCS) SSURGO soils database, the corresponding soil unit can be mapped in a geographic information system software. The latest version of the SSURGO database should be used to get the most accurate join. Data is updated yearly from both NRCS and from AGM, however, NYSERDA will not update this dataset and it will remain intact for future reference. NYSERDA intends on creating new soils datasets for future procurements on an annual basis.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.