The Food Access Research Atlas presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility, provides food access data for populations within census tracts, and offers census-tract-level data on food access that can be downloaded for community planning or research purposes.

The Food Access Research Atlas: Presents an overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility; Provides food access data for populations within census tracts; and Offers census-tract-level data on food access that can be downloaded for community planning or research purposes.

What can you do with the Atlas? Create maps showing food access indicators by census tract using different measures and indicators of supermarket accessibility; Compare food access measures based on 2019 data with the previous 2015 measures; View indicators of food access for selected subpopulations; and Download census-tract-level data on food access measures.

2015 USDA Food Desert areas for Florida defined by 2010 US Census tract. Based on LILATract_1And10 field census data. Developed by the USDA Economic Research Service (ERS) as part of the Food Access Research Atlas.This service is intended for use with popups or at very large scales.This data layer is part of Florida’s Roadmap to Living Healthy web map produced by the Florida Department of Agriculture and Consumer Services (FDACS), Division of Food, Nutrition and Wellness (DFNW).For technical assistance, contact the Florida's Roadmap to Healthy Living Administrator

Dataset is an overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. This dataset provides food access data for populations within census tracts; and offers census-tract-level data on food access that can be used for community planning or research purposes.Data from USDA Economic Research Service (ERS) Food Access Research Atlas, 2019. Last updated 4/27/2021.See also USDA map service at https://gisportal.ers.usda.gov/server/rest/services/FARA/FARA_2019/MapServer.

All data included in the Food Access Research Atlas are aggregated into an Excel spreadsheet for easy download. The Documentation section provides complete information on data sources and definitions. Note for GIS users: The Atlas is based on 2010 census tract polygons. To use the underlying Atlas data in GIS, the data from this spreadsheet needs to be joined to a census tract boundary file. With ESRI software, users should have access to the tract layer on ESRI's "Data and Maps" data distribution. For users of other software, tract boundaries can be downloaded directly from the Census Bureau's Cartographic Boundary Files. The underlying map services used in the Food Access Research Atlas are also available for both developers and GIS users.

description: All of the ERS mapping applications, such as the Food Environment Atlas and the Food Access Research Atlas, use map services developed and hosted by ERS as the source for their map content. These map services are open and freely available for use outside of the ERS map applications. Developers can include ERS maps in applications through the use of the map service REST API, and desktop GIS users can use the maps by connecting to the map server directly.; abstract: All of the ERS mapping applications, such as the Food Environment Atlas and the Food Access Research Atlas, use map services developed and hosted by ERS as the source for their map content. These map services are open and freely available for use outside of the ERS map applications. Developers can include ERS maps in applications through the use of the map service REST API, and desktop GIS users can use the maps by connecting to the map server directly.

Limited access to supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food may make it harder for some Americans to eat a healthy diet. Expanding the availability of nutritious and affordable food by developing and equipping grocery stores, small retailers, corner markets and farmers’ markets in communities with limited access is an important part of the Healthy Food Financing Initiative. There are many ways to define which areas are considered "food deserts" and many ways to measure food store access for individuals and for neighborhoods. Most measures and definitions take into account at least some of the following indicators of access:

• Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area.
• Individual-level resources that may affect accessibility, such as family income or vehicle availability.
• Neighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.

In the Food Access Research Atlas, several options are available to describe food access along these dimensions. The Food Access Research Atlas presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. It provides food access data for populations within census tracts and offers census-tract-level data on food access that can be downloaded for community planning or research purposes. This Atlas can be used to create maps showing food access indicators by census tract using different measures and indicators of supermarket accessibility. It can be used to compare food access measures based on 2015 data with the previous 2010 measures, view indicators of food access for selected subpopulations, and download census-tract-level data on food access measures.

Please find attached the data documentation. The Atlas is based on 2010 census tract polygons. To use the underlying Atlas data in a GIS, the data from this spreadsheet needs to be joined to a census tract boundary file. With ESRI software, users should have access to the tract layer on ESRI's "Data and Maps" data distribution. For users of other software, tract boundaries can be downloaded directly from the Census Bureau's Cartographic Boundary Files. The underlying map services used in the Food Access Research Atlas are also available for both developers and GIS users. See the Geospatial API documentation for more information.

The Food Access Research Atlas (FARA), developed by the U.S. Department of Agriculture’s Economic Research Service (USDA ERS), is a spatial dataset and mapping tool designed to analyze food access disparities. It provides census tract-level data on low-income and low-access areas, using metrics like proximity to supermarkets and vehicle availability. The dataset identifies regions where populations face barriers to affordable, healthy food, often termed "food deserts." FARA supports research, policy development, and community planning by offering customizable maps and downloadable data for U.S. census tracts. Key features include comparisons of food access between 2015 and 2019, alternative definitions of low-income thresholds, and geospatial APIs for integration into GIS systems. Unique aspects include contextual data on demographic factors (e.g., income, population density) and accessibility metrics, enabling nuanced analysis of food insecurity drivers. The tool also distinguishes between urban, suburban, and rural access challenges. Created to expand on earlier "Food Desert Locator" efforts, FARA aims to inform interventions addressing food system inequities. Its open-access data and user-friendly interface cater to researchers, policymakers, and local organizations seeking evidence-based solutions.

This map runs on this app: http://nmcdc.maps.arcgis.com/home/item.html?id=2088cfcae5e84568bee211db7e226c28This map now includes updated Limited Food Access measures from the USDA, and income and poverty measures from the American Community Survey. Read the USDA's latest study (May, 2016) about access to food resources and the impact on nutrition - Recent Evidence on the Effects of Food Store Access on Food Choice and Diet QualityThe map shows the locations and categorizations of food licenses in New Mexico, updated in February 2016. The 2012 version can still be explored on the map. Categories include: Missions/Shelters, Produce/Growers Markets, Meat Markets, Delis, Prepackage/Convenience Stores, Fast Food, and Grocery Stores. The map also shows areas within 1 mile of a grocery store. The locations and schedules of the 2016 Farmers and Growers Markets, Double-Up Food Books sties, SNAP redemption stores, and Children's Summer Meals sites are displayed as well.Not included are food establishments on the Navajo Nation and some other tribal lands. For feedback or data requests contact nmcommunitydatacollaborative@gmail.com

This layer represents USDA Food Access Research Atlas data at the census tract geography. Low Income is defined as tracts with a poverty rate of 20% or higher, or tracts with median family income less than 80% of median family income of the state or metropolitan area. Low Access is defined as tracts where a significant number or share of residents is more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket.http://www.ers.usda.gov/data-products/food-access-research-atlas/go-to-the-atlas.aspxFood accessLimited access to supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food may make it harder for some Americans to eat a healthy diet. There are many ways to measure food store access for individuals and for neighborhoods, and many ways to define which areas are food deserts—neighborhoods that lack healthy food sources. Most measures and definitions take into account at least some of the following indicators of access:Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area.Individual-level resources that may affect accessibility, such as family income or vehicle availability.Neighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.In the Food Access Research Atlas, several indicators are available to measure food access along these dimensions. For example, users can choose alternative distance markers to measure low access in a neighborhood, such as the number and share of people more than half a mile to a supermarket or 1 mile to a supermarket. Users can also view other census-tract-level characteristics that provide context on food access in neighborhoods, such as whether the tract has a high percentage of households far from supermarkets and without vehicles, individuals with low income, or people residing in group quarters.Low-income neighborhoodsThe criteria for identifying a census tract as low income are from the Department of Treasury’s New Markets Tax Credit (NMTC) program. This program defines a low-income census tract as any tract where:The tract’s poverty rate is 20 percent or greater; orThe tract’s median family income is less than or equal to 80 percent of the State-wide median family income; orThe tract is in a metropolitan area and has a median family income less than or equal to 80 percent of the metropolitan area's median family income.Low-access census tractsIn the Food Access Research Atlas, low access to healthy food is defined as being far from a supermarket, supercenter, or large grocery store ("supermarket" for short). A census tract is considered to have low access if a significant number or share of individuals in the tract is far from a supermarket.In the original Food Desert Locator, low access was measured as living far from a supermarket, where 1 mile was used in urban areas and 10 miles was used in rural areas to demarcate those who are far from a supermarket. In urban areas, about 70 percent of the population was within 1 mile of a supermarket, while in rural areas over 90 percent of the population was within 10 miles (see Access to Affordable and Nutritious Food: Updated Estimates of Distance to Supermarkets Using 2010 Data). Updating the original 1- and 10-mile low-access measure shows that an estimated 18.3 million people in these low-income and low-access census tracts were far from a supermarket in 2010.Three additional measures of food access based on distance to a supermarket are provided in the Atlas:One additional measure applies a 0.5-mile demarcation in urban areas and a 10-mile distance in rural areas. Using this measure, an estimated 52.5 million people, or 17 percent of the U.S. population, have low access to a supermarket;A second measure applies a 1.0-mile demarcation in urban areas and a 20-mile distance in rural areas. Under this measure, an estimated 16.5 million people, or 5.3 percent of the U.S. population, have low access to a supermarket; andA slightly more complex measure incorporates vehicle access directly into the measure, delineating low-income tracts in which a significant number of households are located far from a supermarket and do not have access to a vehicle. This measure also includes census tracts with populations that are so remote, that, even with a vehicle, driving to a supermarket may be considered a burden due to the great distance. Using this measure, an estimated 2.1 million households, or 1.8 percent of all households, in low-income census tracts are far from a supermarket and do not have a vehicle. An additional 0.3 million people are more than 20 miles from a supermarket.For each of the first three measures that are based solely on distance, a tract is designated as low access if the aggregate number of people in the census tract with low access is at least 500 or the percentage of people in the census tract with low access is at least 33 percent. For the final measure using vehicle availability, a tract is designated as having low vehicle access if at least one of the following is true:at least 100 households are more than ½ mile from the nearest supermarket and have no access to a vehicle; orat least 500 people or 33 percent of the population live more than 20 miles from the nearest supermarket, regardless of vehicle access.Methods used to assess distance to the nearest supermarket are the same for each of these measures. First, the entire country is divided into ½-km square grids, and data on the population are aerially allocated to these grids (see Access to Affordable and Nutritious Food: Updated Estimates of Distance to Supermarkets Using 2010 Data). Then, distance to the nearest supermarket is measured for each grid cell by calculating the distance between the geographic center of the ½-km square grid that contains estimates of the population (number of people and other subgroup characteristics) and the center of the grid with the nearest supermarket.Once the distance to the nearest supermarket is calculated for each grid cell, the estimated number of people or housing units that are more than 1 mile from a supermarket in urban tracts, or 10 miles in rural census tracts, is aggregated at the census-tract level (and similarly for the alternative distance markers). A census tract is considered rural if the population-weighted centroid of that tract is located in an area with a population of less than 2,500; all other tracts are considered urban tracts.Food desertsThe Food Access Research Atlas maps census tracts that are both low income (li) and low access (la), as measured by the different distance demarcations. This tool provides researchers and other users multiple ways to understand the characteristics that can contribute to food deserts, including income level, distance to supermarkets, and vehicle access.Additional tract-level indicators of accessVehicle availabilityA tract is identified as having low vehicle availability if more than 100 households in the tract report having no vehicle available and are more than 0.5 miles from the nearest supermarket. This corresponds closely to the 80th percentile of the distribution of the number of housing units in a census tract without vehicles at least 0.5 miles from a supermarket (the 80th percentile value was 106 housing units). This means that about 20 percent of all census tracts had more than 100 housing units that were 0.5 miles from a supermarket and without a vehicle. This indicator was applied to both urban and rural census tracts.Overall, 8.8 percent of all housing units in the United States do not have a vehicle, and 4.2 percent of all housing units are at least 0.5 mile from a store and without a vehicle. Vehicle availability is defined in the American Community Survey as the number of passenger cars, vans, or trucks with a capacity of 1-ton or less kept at the home and available for use by household members. The number of available vehicles includes those vehicles leased or rented for at least 1 month, as well as company, police, or government vehicles that are kept at home and available for non-business use.Whether a vehicle is available to a household for private use is an important additional indicator of access to healthy and affordable food. For households living far from a supermarket or large grocery store, access to a private vehicle may make accessing these retailers easier than relying on public or alternative means of transportation.Group quarters populationUsers may be interested in highlighting tracts with large shares of people living in group quarters. Group quarters are residential arrangements where an entity or organization owns and provides housing (and often services) for individuals residing in these buildings. This includes college dormitories, military quarters, correctional facilities, homeless shelters, residential treatment centers, and assisted living or skilled nursing facilities. These living arrangements frequently provide dining and food retail solely for their residents. While individuals living in these areas may appear to be far from a supermarket or grocery store, they may not truly experience difficulty accessing healthy and affordable food. Tracts in which 67 percent of individuals or more live in group quarters are highlighted.General tract characteristicsPopulation, tract totalGeographic level: census tractYear of data: 2010Definition: Total number of individuals residing in a tract.Data sources: Data are from the 2012 report, Access to Affordable and Nutritious Food: Updated Estimates of Distances to Supermarkets Using 2010 Data. Population data are reported at the block level from the 2010 Census of Population and Housing. These data were aerially allocated down to ½-kilometer-square grids across the United States.Low-income tractGeographic level: census tractYear of data: 2010Definition: A tract with either a poverty rate of 20

Map service contains maps relevant to Low-income, low access to supermarkets, and other related issues. Last updated: January 11, 2017.The Food Access Research AtlasData developed by the USDA Economic Research Service. Details are available here: http://www.ers.usda.gov/data-products/food-access-research-atlas/documentation.aspxFor general information please visit:http://www.ers.usda.gov/

This EnviroAtlas dataset contains a count of the number of local farmers markets within each subwatershed (12-digit HUC) based on their location given within the USDA National Farmers Market Directory (https://www.ams.usda.gov/local-food-directories/farmersmarkets). This data has been processed from the original directory to remove duplicate locations, as well as a small subsample (25 markets) were corrected by hand in order avoid duplication across block group boundaries. This dataset is contemporary as of 5/20/2016, and downloaded from the USDA Agricultural Marketing Service (AMS) website. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Healthy Access Locator map can be used to view schools that have received a Healthier US Schools Challenge Award (HUSSC). To get started, click on Search Awards and enter your search criteria. When the information displays on the map, you can click a star for additional details or see a summary of your results below the map. You can also use the Data Layers feature to display different data layers on obesity and diabetes prevalence, SNAP Participation Rates, and SNAP Outreach Plans by states. (HUSSC Awards as of May 30, 2013).

SNAP is the largest nutrition assistance program in the US. Understanding where SNAP dollars can be redeemed is thus a critical part of understanding food access environments. Data compiled from the USDA Food and Nutrition Service SNAP Retail locator downloaded in January 2022. https://www.fns.usda.gov/snap/retailer-locatorXY coordinates for each retailer were re-verified using google maps due to geocoding inaccuracies in the USDA database. Retailers are categorized into five types of stores. “Big Box” are large commercial retail chains (superstores) that sell a range of products such asclothing, electronics, furniture, hardware, household supplies, pharmaceuticals and groceries. “Grocery” are retailers that primarily sell food and are distinguished from their counterparts byoffering a wide diversity of perishable and nonperishable items including vegetables, fruit, meat, poultry,fish, bread and cereal, and dairy products. Most grocery stores are WIC approved. “Small Box” are retail store chains that sell a range standardized food products with minimal perishable options along with clothing,electronics, hardware, household supplies and pharmaceuticals. “Convenience” are retail locations that stock prepared food items, snacks, beverages, and only a very limited range of foods for home preparation.“Farmers Markets” sell agricultural produce including vegetables,fruits, meats, poultry, and dairy products usually in the form of direct farm to consumer sales. “Specialty” retailers carry limited food items focusing on a select product types such as international foods, butcheries, bakeries etc. All stores were called to identify whether they carry fresh produce and accept WIC payments. These categories are reflected in the data as well.

This EnviroAtlas dataset contains a count of the number of local farmers markets within each census block group (CBG) based on their location given within the USDA National Farmers Market Directory (https://www.ams.usda.gov/local-food-directories/farmersmarkets). This data has been processed from the original directory to remove duplicate locations, as well as a small subsample (25 markets) were corrected by hand in order avoid duplication across block group boundaries. This dataset is contemporary as of 5/20/2016, and downloaded from the USDA Agricultural Marketing Service (AMS) website. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

NUOnet Vision: Efficient use of nutrients to optimize production and product quality of food for animals and humans, fuel and fiber in a sustainable manner that contributes to ecosystem services. This record contains the DET and Data Dictionary for NUOnet - the data files may be found at https://usdaars.maps.arcgis.com/apps/MapSeries/index.html?appid=e90392a99d5c427487c6c37cf6d47844 Best nutrient management practices are critical for maintaining profitable economic returns, sustaining higher yields, lowering environmental impacts, optimizing nutritional quality, and providing ecosystem services. Best management practices that improve nutrient use efficiencies can reduce nutrient losses from agricultural systems. However, we need to improve our understanding of biological, physical and chemical influences on nutrient processes. For instance, crop use efficiency of nitrogen (N), the primary macronutrient regulating yield and protein content, can be reduced by processes such as denitrification (N2O and N2 emission), leaching (NH4-N, NO3-N, and organic-N), ammonia (NH3-N,) volatilization, surface runoff and erosion, disease, and non-crop competition. Similarly, we need to obtain more information about biological and physical cycles of nutrients, especially phosphorus (P), including factors that influence nutrient availability from fertilizers, crop residues, cover crops, manures, and other byproducts. We need a better understanding of relationships between soil biological communities and ecosystems, including plant roots and root exudates, and availability and uptake of macro- and micro-nutrients. In addition, we need information regarding how these practices impact yields, organoleptic qualities, and the macro- and micro-nutritional composition of plants. This information will improve our ability to develop best nutrient management practices. Optimal soil nutrient levels are critical for maximizing economic returns, increasing sustainable yields, lowering environmental impacts, sustaining ecosystem services and optimizing nutritional and organoleptic qualities of human and animal foods. Efficient management practices are crucial for increasing economic returns for land managers in a sustainable manner while producing high quality of food for animals and humans with reduced off-site transfer of nutrients from agricultural areas in watersheds. Optimizing N and P inputs requires more information about nutrient inputs from fertilizers, manures, composts, agricultural byproducts, cover crops, and other nutrient sources in addition to nutrient cycling within soils. This requires data from long-term nutrient management studies across a wide range of soils, crops, and environmental conditions. Land management needs are to connect nutrient management practices for crops with nutrient use efficiency; crop quality; crop chemical composition and nutritional value, quality and acceptability for animal and human health. Development of databases that enable the scientific exploration of connections among data generated from diverse research efforts such as nutrient management, fate and ecosystem service outcomes, nutritional composition of crops, and animal and human health, is needed. Nitrogen is a key nutrient that enhances agricultural yield and protein content, but multiple N loss pathways, as previously mentioned, reduce crop N use efficiency (NUE). Implementing proper management practices is needed to reduce N losses from agricultural systems. ARS has multidisciplinary scientific teams with expertise in soils, ecological engineering, hydrology, livestock management and nutrition, horticulture, crop breeding, human and animal nutrition, post-harvest management and processing, and other areas, and intentional collaboration among these teams offers opportunities to rapidly improve NUE and crop quality and reduce off-site N losses. Similarly, increased P use efficiencies are needed to enhance and ensure sustainable agricultural production and to reduce environmental degradation of water sources. Manure is a valuable source of P and it can be used as a soil amendment to reduce crop production costs. However, there is a need to improve our understanding of the biological and physical cycles of soil P, as well as to obtain more information about P supplies from fertilizer, crop residues, cover crops, manure, and byproducts, and livestock nutrition impacts on manure properties. There is also a need for a better understanding of soil biological communities and ecosystems, including plant roots and root exudates and how their interactions with crops and community ecology affect yield and the uptake of macro- and micro-nutrients and the ultimate nutritional composition and organoleptic qualities of the crop. Studies documenting the responses of crop-associated biological communities to management practices and genetic technologies implemented across multiple environments (e.g., soil types and chemistries, hydrologic regimes, climates) will improve our understanding of gaps in macro- and micro-nutrient management strategies. A goal of the USDA-ARS is to increase agricultural production and quality while reducing environmental impacts. The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows. Increasing our understanding of stocks and flows could help in the identification of knowledge gaps as well as areas where increased efficiencies can be achieved at a national level. NUOnet could also be used to develop tools to derive cost-benefit curves associated with nutrient management improvement scenarios and assess local, regional and national impacts of off-site nutrient loss. Understanding how agricultural production impacts human health is a challenge, and the database could be used to link crop management strategies to crop chemical composition to human consumption patterns and ultimately to human health outcomes. A national database will also be very important for development and evaluation of new technologies such as real-time sensing or other proximal and remote sensing technologies that enable assessment of nutrient use efficiencies, particularly at the grower level. The database could also be used to develop analyses that will contribute to the recommendation of policies for resource allocations that will most effectively fulfill the goals of the Grand Challenge. Such a national database with contributions from peers across different national programs could also enhance collaborations between ARS, universities, and extension specialists, as well as with producers, industry, and other partners. See the NUOnet Home Page for more information about this database and strategic goals. Resources in this dataset:Resource Title: GRACEnet-NUOnet Data Dictionary. File Name: GRACEnet-NUOnet_DD.csvResource Title: NUOnet Data Entry Template. File Name: DET_NATRES_NUO.zipResource Description: A multi-tab worksheet for data entry. Users can customize fields to be mandatory, set minimum and maximum values, and run a validation on fields as specified by the user. https://gpsr.ars.usda.gov/html/NUOnet_DET/DET_NATRES_NUO.xlsm

This dataset represents food environment indicators and risk assessment for all Colorado census tracts and was published by the USDA Economic Research Service in 2017, although the data used in this assessment represents 2010-2015. These data help to ascertain community-level:Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area.Resources that may affect accessibility, such as family income or vehicle availability.Indicators of resources, such as the average income of the neighborhood and the availability of public transportation.This dataset presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility, provides food access data for populations within census tracts; and offers census-tract-level data on food access that can be downloaded for community planning or research purposes. Further documentation on the assembly of these data can be found here.

This dataset contains research data compiled by the “Managing Water for Increased Resiliency of Drained Agricultural Landscapes” project a.k.a. Transforming Drainage. This project was funded from 2015-2021 by the United States Department of Agriculture, National Institute of Food and Agriculture (USDA-NIFA, Award No. 2015-68007-23193). Data are also available from a separate web-accessible application (drainagedata.org). At drainagedata.org, users can visualize the data with customized tools, query based on specific sites and measurements of interest, and access site photographs, maps, summaries, and publications. Additional data or edits made following the publication of this data here at USDA NAL Ag Data Commons will be posted under the Versions tab on drainagedata.org. These data began in 1996 and include plot- and field-level measurements for 39 experiments across the Midwest and North Carolina. Practices studied include controlled drainage, drainage water recycling, and saturated buffers. In total, 219 variables are reported and span 207 site-years for tile drainage, 154 for nitrate-N load, 181 for water quality, 92 for water table, and 201 for crop yield. The Transforming Drainage Project worked to advance the process of designing and implementing agricultural drainage systems for storing water in the landscape to improve the resiliency and productivity of agricultural systems. At each site, a control plot was paired with a plot with one of the following three practices to assess impacts. Controlled Drainage (CD) is the practice of using a water control structure to raise the depth of the drainage outlet, holding water in the field during periods when drainage is not needed. Drainage Water Recycling (DWR) diverts subsurface drainage water into on-farm ponds or reservoirs, where it is stored until it can be used by the crop later in the season through supplemental irrigation. Saturated Buffers (SB) remove nitrate from subsurface drainage water by diverting it into the buffer where it can be taken up by growing vegetation or removed by denitrification. Resources in this dataset:Resource Title: Field management - tillage. File Name: mngt_tillage_data.csvResource Description: Information about tillage operations performed in the research fields during the study periodResource Title: Field management – notes. File Name: mngt_notes_data.csvResource Description: General information about field conditions during the study periodResource Title: Field management – residue. File Name: mngt_residue_data.csvResource Description: Information about residue management in the research fields during the study periodResource Title: Field management – fertilizing. File Name: mngt_fertilizing_data.csvResource Description: Information about fertilizer application and soil amendments performed in the research fields during the study periodResource Title: Field management – harvesting. File Name: mngt_harvesting_data.csvResource Description: Information about harvesting operations performed in the research fields during the study periodResource Title: Field management – planting. File Name: mngt_planting_data.csvResource Description: Information about planting operations performed in the research fields during the study periodResource Title: Field management – irrigation. File Name: mngt_irrigation_data.csvResource Description: Information about irrigation operations performed in the research fields during the study periodResource Title: Field management – drainage water management. File Name: mngt_dwm_data.csvResource Description: Information about drainage water management in the research fields during the study periodResource Title: Weather data. File Name: weather_data.csvResource Description: On-site weather data collected in the research fields during the study periodResource Title: Soil physicochemical properties data. File Name: soil_properties_data.csvResource Description: Soil physicochemical measurements collected in the research fields during the study periodResource Title: Soil moisture data. File Name: soil_moisture_data.csvResource Description: Soil moisture, temperature and bulk EC measurements collected in the research fields during the study periodResource Title: Irrigation data. File Name: irrigation_data.csvResource Description: Amount of irrigation water applied to the research fields during the study periodResource Title: Stage data. File Name: water_stage_data.csvResource Description: Stage measurements in the wetlands during the study periodResource Title: Water table data. File Name: water_table_data.csvResource Description: Water table measurements collected in the research fields during the study periodResource Title: Water quality data. File Name: water_quality_data.csvResource Description: Water quality measurements collected from the research fields during the study periodResource Title: Methodology. File Name: meta_methods.csvResource Description: Description of the drainage system set up, sampling procedures, and other protocols used at each research site during the study periodResource Title: Plot treatment. File Name: meta_treatment_identifier.csvResource Description: List of treatments used across the research sites during the study periodResource Title: Plot description. File Name: meta_plot_characteristics.csvResource Description: Description of plots and corresponding drainage systems for each research siteResource Title: Agronomic data. File Name: agronomic_data.csvResource Description: Agronomic measurements collected in the research fields during the study periodResource Title: Site description. File Name: meta_site_characteristics.csvResource Description: Description of the research sitesResource Title: Drainage data. File Name: drain_flow_and_N_loads_data.csvResource Description: Drain flow and nitrate load measurements collected from the research fields during the study periodResource Title: Data dictionary. File Name: data_dictionary.csv

The Census of Agriculture, produced by the USDA National Agricultural Statistics Service (USDA), provides a complete count of America's farms, ranches and the people who grow our food. The census is conducted every five years, most recently in 2017, and provides an in-depth look at the agricultural industry.This layer summarizes wheat production from the 2017 Census of Agriculture at the county level.This layer was produced from data downloaded using the USDA's QuickStats Application. The data was transformed using the Pivot Table tool in ArcGIS Pro and joined to the county boundary file provided by the USDA. The layer was published as feature layer in ArcGIS Online. Dataset SummaryPhenomenon Mapped: 2017 Wheat ProductionCoordinate System: Web Mercator Auxiliary SphereExtent: 48 Contiguous United StatesVisible Scale: All ScalesSource: USDA National Agricultural Statistics Service QuickStats ApplicationPublication Date: 2017AttributesThis layer provides values for the following attributes. Note that some values are not disclosed (coded as -1 in the layer) to protect the privacy of producers in areas with limited production.Area Harvested in AcresOperations with Area HarvestedOperations with SalesProduction in BushelsSales in US DollarsIrrigated Area Harvested in AcresOperations with Irrigated Area HarvestedAdditionally attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.Many other ready-to-use layers derived from the Census of Agriculture can be found in the Living Atlas Agriculture of the USA group.What can you do with this layer?This layer can be used throughout the ArcGIS system. Feature layers can be used just like any other vector layer. You can use feature layers as an input to geoprocessing tools in ArcGIS Pro or in Analysis in ArcGIS Online. Combine the layer with others in a map and set custom symbology or create a pop-up tailored for your users. For the details of working with feature layers the help documentation for ArcGIS Pro or the help documentation for ArcGIS Online are great places to start. The ArcGIS Blog is a great source of ideas for things you can do with feature layers. This layer is part of ArcGIS Living Atlas of the World that provides an easy way to find and explore many other beautiful and authoritative layers, maps, and applications on hundreds of topics.