Introduction and Rationale: Due to our increasing understanding of the role the surrounding landscape plays in ecological processes, a detailed characterization of land cover, including both agricultural and natural habitats, is ever more important for both researchers and conservation practitioners. Unfortunately, in the United States, different types of land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this data gap and reduce duplicative efforts in geospatial processing, we merged two major datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce an integrated land cover map. Our workflow leveraged strengths of the NVC and the CDL to produce detailed rasters comprising both agricultural and natural land-cover classes. We generated these maps for each year from 2012-2021 for the conterminous United States, quantified agreement between input layers and accuracy of our merged product, and published the complete workflow necessary to update these data. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved a majority of these conflicts based on surrounding agricultural land, leaving only 0.6% of agricultural pixels unresolved in our merged product. Contents: Spatial data Attribute table for merged rasters Technical validation data Number and proportion of mismatched pixels Number and proportion of unresolved pixels Producer's and User's accuracy values and coverage of reference data Resources in this dataset:Resource Title: Attribute table for merged rasters. File Name: CombinedRasterAttributeTable_CDLNVC.csvResource Description: Raster attribute table for merged raster product. Class names and recommended color map were taken from USDA-NASS Cropland Data Layer and LANDFIRE National Vegetation Classification. Class values are also identical to source data, except classes from the CDL are now negative values to avoid overlapping NVC values. Resource Title: Number and proportion of mismatched pixels. File Name: pixel_mismatch_byyear_bycounty.csvResource Description: Number and proportion of pixels that were mismatched between the Cropland Data Layer and National Vegetation Classification, per year from 2012-2021, per county in the conterminous United States.Resource Title: Number and proportion of unresolved pixels. File Name: unresolved_conflict_byyear_bycounty.csvResource Description: Number and proportion of unresolved pixels in the final merged rasters, per year from 2012-2021, per county in the conterminous United States. Unresolved pixels are a result of mismatched pixels that we could not resolve based on surrounding agricultural land (no agriculture with 90m radius).Resource Title: Producer's and User's accuracy values and coverage of reference data. File Name: accuracy_datacoverage_byyear_bycounty.csvResource Description: Producer's and User's accuracy values and coverage of reference data, per year from 2012-2021, per county in the conterminous United States. We defined coverage of reference data as the proportional area of land cover classes that were included in the reference data published by USDA-NASS and LANDFIRE for the Cropland Data Layer and National Vegetation Classification, respectively. CDL and NVC classes with reference data also had published accuracy statistics. Resource Title: Data Dictionary. File Name: Data_Dictionary_RasterMerge.csv

Vietnam: Land area in sq. km: The latest value from 2022 is 313429 sq. km, unchanged from 313429 sq. km in 2021. In comparison, the world average is 673036 sq. km, based on data from 191 countries. Historically, the average for Vietnam from 1961 to 2022 is 320717 sq. km. The minimum value, 310070 sq. km, was reached in 2003 while the maximum of 325490 sq. km was recorded in 1961.

Land Cover Map 2021 (LCM2021) is a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2021. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2021. Land cover maps describe the physical material on the surface of the country. For example grassland, woodland, rivers & lakes or man-made structures such as roads and buildingsThis is a 10 m Classified Pixel dataset, classified to create a single mosaic of national cover. Provenance and quality:UKCEH’s automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2021 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy.View full metadata information and download the data at catalogue.ceh.ac.uk

This is a web map service (WMS) for the 10-metre Land Cover Map 2023. The map presents the and surface classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats.UKCEH’s automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2020 to 2022. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2023 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy.

The Map Service Viewer is a web-based mapping tool designed to allow users to view the Forest Service Land Status Record System (LSRS) data. The LSRS data published via this map service is considered to be the authoritative source for Forest Service ownership. The data is designed to provide land status information necessary to manage National Forest System lands and natural resources. For more information please visit the US Forest Service Lands and Realty Management Program site.

Monaco: Land area in sq. km: The latest value from 2022 is 2 sq. km, unchanged from 2 sq. km in 2021. In comparison, the world average is 673036 sq. km, based on data from 191 countries. Historically, the average for Monaco from 1961 to 2022 is 2 sq. km. The minimum value, 2 sq. km, was reached in 1961 while the maximum of 2 sq. km was recorded in 1961.

For a detailed view of Alaska, please reference the BIA AIAN LAR (Alaska Detail) Map here: https://bia-geospatial.maps.arcgis.com/sharing/rest/content/items/c914b3914c97440f9e90d142be55a683/data. The purpose of the American Indian and Alaska Native Land Area Representation (AIAN-LAR) Geographic Information System (GIS) dataset is to depict the exterior extent of land held in “trust” or “restricted fee” status by the United States for a tribe(s) and individual Indians of federally recognized Tribes. A tribe is a tribe, band, pueblo, community or other federally acknowledged group of Indians. A federally recognized tribe is an American Indian or Alaska Native tribal entity that is recognized as having a government-to-government relationship with the United States, with the responsibilities, powers, limitations, and obligations attached to that designation, and are eligible for funding and services from the BIA. Furthermore, federally recognized tribes are recognized as possessing certain inherent rights of self-government (i.e., tribal sovereignty) and are entitled to receive certain federal benefits, services, and protections because of their special relationship with the United States. At present, there are 574 federally recognized American Indian and Alaska Native tribes and villages. Not all federally recognized Tribes have a designated land area, land in trust or restricted status and therefore may not have an associated land area represented in the AIAN-LAR. Not all land areas such as public domain allotments are under the jurisdiction or associated with any particular federally recognized tribe. The BIA publishes an updated list of federally recognized tribes in a federal register notice. These data are public information and may be used and interpreted by organizations, agencies, units of government, or other entities. The user, agency or organization has sole responsibility for ensuring the appropriate use, application, integration and republication of these data. The most recent federal register notice is located at: https://www.federalregister.gov/documents/2023/01/12/2023-00504/indian-entities-recognized-by-and-eligible-to-receive-services-from-the-united-states-bureau-of

The USA: Agricultural land, sq. km.: The latest value from 2021 is 4058104 sq. km., unchanged from 4058104 sq. km. in 2020. In comparison, the world average is 245857 sq. km., based on data from 193 countries. Historically, the average for the USA from 1961 to 2021 is 4220416 sq. km.. The minimum value, 4030811 sq. km., was reached in 2012 while the maximum of 4475090 sq. km. was recorded in 1961.

Best way to search the dataset - use box at the top right of page. This data reflects New Jersey's Property Taxes that are assessed on an annual basis by the local assessor then submitted to their county board of taxation. This data contains the collection of those lists filed in January of each new calendar year. Any changes, like ownership transfer, that occur after that date will not be reflected in this file.

Composite map of Future Land Use. This is a pdf document.

Summary Data Table for Land Cover in AG and Rural Residential zones. Data created 3/2018 by Spatial Alternatives for The Ad-Hoc Committee on Auburn's Agriculture and Natural Resource. Data source: 2013 Aerial Imagery. Source 2013 Aerial Imagery.See also Land Cover PDF Maps.

This dataset consists of the vector version of the Land Cover Map 2015 (LCM2015) for Great Britain. The vector data set is the core LCM data set from which the full range of other LCM2015 products is derived. It provides a number of attributes including land cover at the target class level (given as an integer value and also as text), the number of pixels within the polygon classified as each land cover type and a probability value provided by the classification algorithm (for full details see the LCM2015 Dataset Documentation). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.

Agricultural land (sq. km) in North America was reported at 4628017 sq. Km in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. North America - Agricultural land (sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Agricultural land (% of land area) in Channel Islands was reported at 43.28 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Channel Islands - Agricultural land (% of land area) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Map showing the General Plan Land Use for the City of San Marcos. For additional information, please visit the City's website.

This bar chart displays land area (km²) by date using the aggregation sum in Georgia. The data is filtered where the date is 2021. The data is about countries per year.

We present a land use management map for Europe. This map is subject to updates, the updates are described in the pdf description. The land use management map is based on the land cover (base map) which has nine different land covers for Europe. The land use management map further divides these land covers into 20 land use management classes based on different inputs. The map is made to be used as a baseline of land use in Europe for land use modelling.

This data set provides four land cover and ecosystem classification maps for northern Alaska. The maps were produced for several projects and from different data sources including Landsat imagery and existing maps and models, and cover a range of ecosystem and vegetation classes. The data used to derive the maps covered the period 1976-08-04 to 2014-09-01.

This Web Mapping Application mirrors the printed Future Land Use Map approved by the Council in resolution R24-0292

This dataset consists of the 25m raster version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 25m raster product consists of two bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target habitat classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. The 25m raster is the most detailed of the LCM2015 raster products both thematically and spatially, and it is used to derive the 1km products. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.