This metadata report documents tabular data sets consisting of items from the Census of Agriculture. These data are a subset of items from county-level data (including state totals) for the conterminous United States covering the census reporting years (every five years, with adjustments for 1978 and 1982) beginning with the 1950 Census of Agriculture and ending with the 2012 Census of Agriculture. Historical (1950-1997) data were extracted from digital files obtained through the Intra-university Consortium on Political and Social Research (ICPSR). More current (1997-2012) data were extracted from the National Agriculture Statistical Service (NASS) Census Query Tool for the census years of 1997, 2002, 2007, and 2012. Most census reports contain item values from the prior census for comparison. At times these values are updated or reweighted by the reporting agency; the Census Bureau prior to 1997 or NASS from 1997 on. Where available, the updated or reweighted data were used; otherwise, the original reported values were used. Changes in census item definitions and reporting as well as changes to county areas and names over the time span required a degree of manipulation on the data and county codes to make the data as comparable as possible over time. Not all of the census items are present for the entire 1950-2012 time span as certain items have been added since 1950 and when possible the items were derived from other items by subtracting or combining sub items. Specific changes and calculations are documented in the processing steps sections of this report. Other missing data occurs at the state and (or) county level due to census non-disclosure rules where small numbers of farms reporting an item have acres and (or) production values withheld to prevent identification of individual farms. In general, caution should be exercised when comparing current (2012) data with values reported in earlier censuses. While the 1974-2012 data are comparable, data prior to 1974 will have inflated farm counts and slightly inflated production amounts due to the differences in collection methods, primarily, the definition of a farm. Further discussion on comparability can be found the comparability section of the Supplemental Information element of this metadata report. Excluded from the tabular data are the District of Columbia, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the three county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. Data for independent cities of Virginia prior to 1959 have been included with their surrounding or adjacent county. Please refer to the Supplemental Information element for information on terminology, the Census of Agriculture, the Inter-university Consortium for Political and Social Research (ICPSR), table and variable structure, data comparability, all farms and economic class 1-5 farms, item calculations, increase of farms from 1974 to 1978, missing data and exclusion explanations, 1978 crop irregularities, pastureland irregularities, county alignment, definitions, and references. In addition to the metadata is an excel workbook (VariableKey.xlsx) with spreadsheets containing key spreadsheets for items and variables by category and a spreadsheet noting the presence or absence of entire variable data by year. Note: this dataset was updated on 2016-02-10 to populate omitted irrigation values for Miami-Dade County, Florida in 1997.

This polygon shapefile provides county or county-equivalent boundaries for the conterminous United States and was created specifically for use with the data tables published as Selected Items from the Census of Agriculture for the Conterminous United States, 1950-2012 (LaMotte, 2015). This data layer is a modified version of Historic Counties for the 2000 Census of Population and Housing produced by the National Historical Geographic Information System (NHGIS) project, which is identical to the U.S. Census Bureau TIGER/Line Census 2000 file, with the exception of added shorelines. Excluded from the CAO_STCOFIPS boundary layer are Broomfield County, Colorado, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the 3 county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. The census of agriculture was not taken in the District of Columbia for 1959, but available data indicate few if any farms in that area, the polygon was left in place to preserve the areas of the surrounding counties. Baltimore City, Maryland was combined with Baltimore County and the St. Louis City, Missouri, was combined with St. Louis County. La Paz County, Arizona was combined with Yuma County, Arizona and Cibola County, New Mexico was combined with Valencia County, New Mexico. Minor county border changes were at a level of precision beyond the scope of the data collection. A major objective of the census data tabulation is to maintain a reasonable degree of comparability of agricultural data from census to census. The tabular data collection is from 14 different censuses where definitions and data collection techniques may change over time and while the data are mostly comparable, a degree of caution should be exercised when using the data in analysis procedures. While the data are at a county-level resolution, a regional approach is more appropriate than a county-by-county analysis. The main purpose of this layer is to provide a base to generate a county raster for the allocation of agricultural census values to specific (agricultural) pixels. Vector format is provided so the raster pixel size can be user designated. References cited: LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016. National Historical Geographic Information System, Minnesota Population Center, 2004, Historic counties for the 2000 census of population and housing: Minneapolis, MN, University of Minnesota, accessed 03/18/2013 at http://nhgis.org

The Census of Agriculture highlight key agricultural metrics for US states and counties. Percentage metrics included were calculated as follows: Percent of harvested cropland in cover crops = (cover crops acres)/((harvested cropland)+(failed crops)-(alfalfa))Percent of total tilled cropland using no-till = (no-till acreage)/(no till + reduced till + conventional till)Percent of tilled cropland using conservation tillage = (no till + reduced till acreage)/(no till + reduced till + conventional till)Percent of agricultural land in conservation easement = (conservation easement acres that excludes CRP)/((land in farms) – (CRP WRP FWP CREP acres))Percent of agricultural land in Conservation Reserve Program = (Conservation Reserve Program acres / cropland acres + Conservation Reserve Program acres ))*100Note, that counties for the Census of Agriculture are different than standard US Census Bureau counties; for example, cities in Virginia such as Harrisonburg, VA are rolled into the respective county and counties in Alaska are rolled into regions with their own district/region FIPS codes, etc. Also note, some counties have no data as one or more of the input variables included suppression.These data have been made publicly available from an authoritative source other than this Atlas and data should be obtained directly from that source for any re-use. See the original metadata from the authoritative source for more information about these data and use limitations. The authoritative source of these data can be found at the following location: https://www.nass.usda.gov/Publications/AgCensus/2017/Online_Resources/Ag_Census_Web_Maps/Data_download/index.php

This layer depicts the agriculture/forest districts in Fairfax County. These areas are specially designated for tax purposes. For additional information refer to this web page: https://www.fairfaxcounty.gov/planning-zoning/agricultural-forestal-district Contact: Fairfax County Department of Information Technology GIS DivisionData Accessibility: Publicly AvailableUpdate Frequency: DailyLast Revision Date: 1/1/2000Creation Date: 1/1/2000Feature Dataset Name: GISMGR.PARCELSLayer Name: GISMGR.AF_DISTRICTS

City of Staunton's Agriculture and Forest District

The Crops Suitability Tool combines soil types, aspect (slope orientation), and percentage of slope to determine the best and least suitable sites in which to grow crops in Loudoun County. It includes different types of Agricultural Soils (Prime Farmland, Secondary Cropland, Grassland Agriculture, Orchard Land, Woodland Use and Wildlife) and its grade of suitability for grapes, tree fruits, hops, vegetables, flowers, herbs, small fruits, field crops, pasture and hay.A spatial model uses existing geographic data to predict an outcome. In this application, we combined soil types, aspect (slope orientation), and percentage of slope to determine the best and least suitable site in which to grow crops in Loudoun County, Virginia. It includes different types of Agricultural Soils (Prime Farmland, Secondary Cropland, Grassland Agriculture, Orchard Land, Woodland Use and Wildlife) and its grade of suitability for grapes, tree fruits, hops, vegetables (ethnic crops), flowers, herbs, and small fruits, field crops, pasture, and hay.This tool does not account for the incidence and prevalence of any type of pests (weed, insects, and diseases -nematodes, fungi, bacteria, or viruses) or weather conditions that can affect crops. The accuracy of the predicted outcomes is not 100% (for example: 17B soils in a concave position are not suitable for growing perennial crops or high cash valued crops); therefore, it is highly recommended to contact VCE Loudoun Commercial Horticulturist Beth Sastre to get a soil map report of the property and/or to have a site evaluation for further recommendation.We encourage farmers, beginner farmers, people interested in farming, and realtors to use this tool to make guided decisions before starting a crop for the first time or buying land. If you see major discrepancies while using this tool, please report them.

These data report the percent of agricultural land, within each selected Chesapeake Bay watershed, that is enrolled in the Conservation Reserve Program (CRP), based on county-level data for each year from the U.S. Department of Agriculture Farm Service Agency.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Virginia Coast Reserve (VCR) contains population employed at farms (percent of total) measurements in percent units and were aggregated to a yearly timescale.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

More Metadata

Annual crop data from 1972 to 1998 are now available on EOS-WEBSTER. These data are county-based acreage, production, and yield estimates published by the National Agricultural Statistics Service. We also provide county level livestock, geography, agricultural management, and soil properties derived from datasets from the early 1990s.

 The National Agricultural Statistics Service (NASS), the statistical
 arm of the U.S. Department of Agriculture, publishes U.S., state, and
 county level agricultural statistics for many commodities and data
 series. In response to our users requests, EOS-WEBSTER now provides 27
 years of crop statistics, which can be subset temporally and/or
 spatially. All data are at the county scale, and are only for the
 conterminous US (48 states + DC). There are 3111 counties in the
 database. The list includes 43 cities that are classified as
 counties: Baltimore City, MD; St. Louis City, MO; and 41 cities in
 Virginia.

 In addition, a collection of livestock, geography, agricultural
 practices, and soil properties variables for 1992 is available through
 EOS-WEBSTER. These datasets were assembled during the mid-1990's to
 provide driving variables for an assessment of greenhouse gas
 production from US agriculture using the DNDC agro-ecosystem model
 [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776;
 Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. The data
 (except nitrogen fertilizer use) were all derived from publicly
 available, national databases. Each dataset has a separate DIF.

 The US County data has been divided into seven datasets.

 US County Data Datasets:

 1) Agricultural Management
 2) Crop Data (NASS Crop data)
 3) Crop Summary (NASS Crop data)
 4) Geography and Population
 5) Land Use
 6) Livestock Populations
 7) Soil Properties

United State Department of Agriculture soil information.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Virginia Coast Reserve (VCR) contains farmland acres (total) measurements in acre units and were aggregated to a yearly timescale.

This map shows the 2019 Gross Domestic Product (GDP) for agriculture, forestry, fishing, and hunting. This uses the North American Industry Classification System (NAICS) 11. Examples include crop production; animal production and aquaculture; forestry and logging; fishing, hunting and trapping; and support activities for agriculture and forestry.The size of each symbol shows the GDP for agriculture, forestry, fishing, and hunting. The color represents the percent of a larger geography. For example, counties show the percent of state GDP from agriculture, forestry, fishing, and hunting. States show a percent of region, and Regions show a percent of the national GDP for this NAICS code. This allows us to see which areas contribute to the bigger picture of GDP. You can optionally turn on a layer showing USDA Census of Agriculture figures for Federal spending toward agriculture. This allows us to compare where government money is going in comparison to GDP figures. GDP is the value of goods and services produced within a county. The underlying Living Atlas layer contains 2019 Gross Domestic Product (GDP) estimates from the Bureau of Economic Analysis (BEA) for the nation, regions, states, and counties. Breakdowns by industry available, using North American Industry Classification System (NAICS) groups. Table CAGDP2, downloaded ‎February ‎2, ‎2021.https://www.bea.gov/data/gdp/gdp-county-metro-and-other-areas Null values are either due to the data being unavailable, or not shown to avoid disclosure of confidential information (in these cases, estimates are included in higher-level totals).The percentages of the next highest geography level's GDP are also available, i.e. regions have percentages for nation's GDP, states have percentages of their region's GDP, and counties have percentages of their state's GDP. If the GPD estimate is unavailable, so is the percentage. If a percentage of state is listed as 0.0 but there is a value for GDP, then this value is <0.1, which rounds to zero. Percentages may not add up to 100 due to rounding and null values.Combined Counties:Kalawao County, Hawaii is combined with Maui County. Separate estimates for the jurisdictions making up the combination areas are not available.Virginia combination areas consist of one or two independent cities with 1980 populations of less than 100,000 combined with an adjacent county. The county name appears first, followed by the city name(s). Separate estimates for the jurisdictions making up the combination area are not available. Bedford County, VA includes the independent city of Bedford for all years.Boundaries used to create regions and counties:Boundaries for this layer were created using the Dissolve geoprocessing tool in Pro and the regional and combined county definitions from BEA.

Conventional, FHA, VA, and USDA mortgage loan limits for Madison County in 2025. Includes limits for 1-4 unit properties and historical data.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Virginia Coast Reserve (VCR) contains population employed at farms (percent of total) measurements in percent units and were aggregated to a yearly timescale.

ZOAM-2020-0002, Prime Agricultural Soils and Cluster Subdivision was adopted in June 2024, with an effective date of March 12, 2025, resulted in the amendment ordinances and revised regulations to improved cluster developments and use of prime agricultural soils in the Rural AR-1 and AR-2 Zoning Districts of the Rural Policy Area. The design of clustered residential development will be improved by incorporating natural features, protecting and conserving agriculturally productive prime agriculture soils, allowing for equine and rural economy uses, and further implementing the policies of the Loudoun County 2019 General Plan with respect to clustered residential development in order to guide all future cluster subdivision applications in the Rural North (AR-1) and Rural South (AR-2) Zoning Districts of the Rural Policy Area.As part of the ZOAM's approval, 15 soil types were identified as Prime Farmland Soils. They include the following soils types; 3A, 13B, 17B, 23B, 28B, 31B, 43B, 45B, 55B, 71B, 76B, 90B, 93B, 94B, 95B. All of these soil types are also currently identified as Prime Soils in the current Interpretive Guide to the use of Soils Maps; Loudoun County, VA, which further describes the soil mapping units within the Loudoun County Soils layer. The Interpretive Guide also identifies 3 other soil types as Prime Farmland Soils (17C, 70B, 70C) but for the purpose of this adopted ZOAM are not considered part of the new Prime Farmland Soils (Cluster Subdivision Option).This map shows, in small scale, a subset of the information contained on the individual detailed soil maps for Loudoun County by identifying the soil types that are considered Prime Farmland Soils (Cluster Subdivision Option). Because of its small scale and general soil descriptions, it is not suitable for planning small areas or specific sites, but it does present a general picture of soils in the County, and can show large areas generally suited to a particular kind of agriculture or other special land use. For more detailed and specific soils information, please refer to the detailed soils maps and other information available from the County Soil Scientist. Digital data consists of mapping units of the various soil types found in Loudoun County, Virginia. The data were collected by digitizing manuscript maps derived from USDA soil maps and supplemented by both field work and geological data. Field work for the soil survey was first conducted between 1947 and 1952. Soils were originally shown at the scale of 1:15840 and then redrafted by the County soil scientist to 1:12000; the data were redrafted a final time to fit Loudoun County's base map standard of 1:2400. Although the current data rely heavily on the original soil survey, there have been extensive field checks and alterations to the soil map based on current soil concepts and land use. The data are updated as field site inspections or interpretation changes occur.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Virginia Coast Reserve (VCR) contains farmland acres (total) measurements in acre units and were aggregated to a yearly timescale.