This site provides interactive access to data from NASS, as part of a cooperative effort among USDA, the USDA Regional Pest Management Centers and the NSF Center for Integrated Pest Management (CIPM). All data available have been previously published by NASS and have been consolidated at the state level. Commodity acreages and active ingredient agricultural chemical use (% acres treated, ai/acre/treatment, average number of treatments, ai/acre, total ai used) data are available. All data can be searched by commodity, year, state and active ingredient. For more details on methodology, please see NASS website. Search results can be obtained in web format and as downloadable Excel files. For each individual active ingredient, commodity, year and statistic, dynamic U.S. maps of each use statistic can be generated. Agricultural chemical usage statistic data can also be seen in a graphical format. Currently, this site contains the data from 1990. We will continue to update the database annually. As this site is enhanced, we will also provide means and totals of the statistics over years, states, and commodities. This project is funded by USDA, The Cooperative State Research, Education, and Extension Service (CSREES), project award No. 2001-34366-10324. Resources in this dataset:Resource Title: Agricultural Chemical Use Program Data. File Name: Web Page, url: https://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/#data Since 2009, the release of chemical use surveys is available through Quick Stats. The following materials are available for each survey: highlights fact sheet, a methodology paper, and a set of data tables featuring commonly requested information.

The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). It allows you to customize your query by commodity, location, or time period. You can then visualize the data on a map, manipulate and export the results as an output file compatible for updating databases and spreadsheets, or save a link for future use. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. County level data are also available via Quick Stats. The data include the total crops and cropping practices for each county, and breakouts for irrigated and non-irrigated practices for many crops, for selected States. The database allows custom extracts based on commodity, year, and selected counties within a State, or all counties in one or more States. The county data includes totals for the Agricultural Statistics Districts (county groupings) and the State. The download data files contain planted and harvested area, yield per acre and production. NASS develops these estimates from data collected through:

hundreds of sample surveys conducted each year covering virtually every aspect of U.S. agriculture

the Census of Agriculture conducted every five years providing state- and county-level aggregates Resources in this dataset:Resource Title: Quick Stats database. File Name: Web Page, url: https://quickstats.nass.usda.gov/ Dynamic drill-down filtered search by Commodity, Location, and Date range, beginning with Census or Survey data. Filter lists are refreshed based upon user choice allowing the user to fine-tune the search.

This feature class depicts the boundaries of Land Survey features called sections, defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township. The entire extent of each of these units should be collected, not just the portion on National Forest System lands. This dataset is derived from the USFS Southwestern Region ALP (Automated Lands Program) data Project. This is one of six layers derived from ALP for the purpose of supplying data layers for recourse GIS analysis and data needs within the Forest Service. The six layers are Surface Ownership, Administrative Forest Boundary, District Boundary, Townships, Sections, and Wilderness. There were some gapes in the ALP data so a small portion of this dataset comes from CCF (Cartographic Feature Files) datasets and the USFS Southwestern Region Core Data Project. ALP data is developed from data sources of differing accuracy, scales, and reliability. Where available it is developed from GCDB (Geographic Coordinate Data Base) data. GCDB data is maintained by the Bureau of Land Management in their State Offices. GCDB data is mostly corner data. Not all corners and not all boundaries are available in GCDB so ALP also utilizes many other data sources like CFF data to derive its boundaries. GCDB data is in a constant state of change because land corners are always getting resurveyed. The GCDB data used in this dataset represents a snapshot in time at the time the GCDB dataset was published by the BLM and may not reflect the most current GCDB dataset available. The Forest Service makes no expressed or implied warranty with respect to the character, function, or capabilities of these data. These data are intended to be used for planning and analyses purposes only and are not legally binding with regards to title or location of National Forest System lands.

The 2018 Irrigation and Water Management Survey (formerly called the Farm and Ranch Irrigation Survey) is a follow-on to the 2017 Census of Agriculture by the U.S. Department of Agriculture (USDA). This survey provides the only comprehensive information on irrigation activities and water use across American farms, ranches, and horticultural operations. In responding to the survey, producers provide information on topics such as water sources and amount of water used, acres irrigated by type of system, irrigation and yield by crop, and system investments and energy costs. The full reports for the 2003, 2008, 2017, and 2018 surveys are provided in this submission. By following the link to the USDA Census of Irrigation, a specific year can be selected, in which the tables and figures of each report are provided.

The dataset, Survey-SR, provides the nutrient data for assessing dietary intakes from the national survey What We Eat In America, National Health and Nutrition Examination Survey (WWEIA, NHANES). Historically, USDA databases have been used for national nutrition monitoring (1). Currently, the Food and Nutrient Database for Dietary Studies (FNDDS) (2), is used by Food Surveys Research Group, ARS, to process dietary intake data from WWEIA, NHANES. Nutrient values for FNDDS are based on Survey-SR. Survey-SR was referred to as the "Primary Data Set" in older publications. Early versions of the dataset were composed mainly of commodity-type items such as wheat flour, sugar, milk, etc. However, with increased consumption of commercial processed and restaurant foods and changes in how national nutrition monitoring data are used (1), many commercial processed and restaurant items have been added to Survey-SR. The current version, Survey-SR 2013-2014, is mainly based on the USDA National Nutrient Database for Standard Reference (SR) 28 (2) and contains sixty-six nutrientseach for 3,404 foods. These nutrient data will be used for assessing intake data from WWEIA, NHANES 2013-2014. Nutrient profiles were added for 265 new foods and updated for about 500 foods from the version used for the previous survey (WWEIA, NHANES 2011-12). New foods added include mainly commercially processed foods such as several gluten-free products, milk substitutes, sauces and condiments such as sriracha, pesto and wasabi, Greek yogurt, breakfast cereals, low-sodium meat products, whole grain pastas and baked products, and several beverages including bottled tea and coffee, coconut water, malt beverages, hard cider, fruit-flavored drinks, fortified fruit juices and fruit and/or vegetable smoothies. Several school lunch pizzas and chicken products, fast-food sandwiches, and new beef cuts were also added, as they are now reported more frequently by survey respondents. Nutrient profiles were updated for several commonly consumed foods such as cheddar, mozzarella and American cheese, ground beef, butter, and catsup. The changes in nutrient values may be due to reformulations in products, changes in the market shares of brands, or more accurate data. Examples of more accurate data include analytical data, market share data, and data from a nationally representative sample. Resources in this dataset:Resource Title: USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES 2013-14 (Survey SR 2013-14). File Name: SurveySR_2013_14 (1).zipResource Description: Access database downloaded on November 16, 2017. US Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES (Survey-SR), October 2015. Resource Title: Data Dictionary. File Name: SurveySR_DD.pdf

This dataset is the soil survey for the City of Buffalo and comes from the Web Soil Survey (WSS), which provides soil data and information produced by the National Cooperative Soil Survey. It is operated by the USDA Natural Resources Conservation Service (NRCS) and provides access to the largest natural resource information system in the world. NRCS has soil maps and data available online for more than 95 percent of the nation’s counties and anticipates having 100 percent in the near future. The site is updated and maintained online as the single authoritative source of soil survey information.

Soil surveys can be used for general farm, local, and wider area planning. Onsite investigation is needed in some cases, such as soil quality assessments and certain conservation and engineering applications. For more detailed information, contact your local USDA Service Center at the following link: https://offices.sc.egov.usda.gov/locator/app?agency=nrcs or your NRCS State Soil Scientist at the following link: http:

SSURGO consists of spatial data and a comprehensive relational database with tables that describe soil properties, interpretations and productivity values. The USDA Natural Resources Conservation Service (NRCS, formerly Soil Conservation Service) provides a download of the statewide SSURGO database that includes vector and raster spatial data, database tables and their relationship classes, and a user guide. To access SSURGO, go to the USDA NRCS Geospatial Data Gateway. To download the database, on the right side of the page, click on the Direct Data Download link under, I Want To... The Direct Data / NAIP Download page will then open. Click on the Soils Geographic Databases link. Then click on the folder named gSSURGO by State (date in folder name). Scroll through the list and select gSSURGO_NJ.zip. Then click on the Download button on the upper right. A message will open that Your Download is In Progress. You will then be prompted to select a file download location.

USDA's National Household Food Acquisition and Purchase Survey (FoodAPS) will provide unique and detailed data about household food choices that are not available from any other survey. FoodAPS is a nationally representative survey of household food purchases and acquisitions.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to documents For complete information, please visit https://data.gov.

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. Data was downloaded Oct 2023 from U.S. Department of Agriculture, Natural Resources Conservation Service. Last Updated 2023.

Quick Stats is the National Agricultural Statistics Service's (NASS) online, self-service tool to access complete results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

This Quarter Section feature class depicts PLSS Second Divisions . PLSS townships are subdivided in a spatial hierarchy of first, second, and third division. These divisions are typically aliquot parts ranging in size from 640 acres to 160 to 40 acres, and subsequently all the way down to 2.5 acres. The data in this feature class was translated from the PLSSSecondDiv feature class in the original production data model, which defined the second division for a specific parcel of land. Metadata

State by state losses reported in the AIA and USDA surveys of states having 6 or more respondents.

In Spring of 2024, the USDA Food and Nutrition Service (FNS) conducted the third survey of supply chain challenges faced by School Food Authorities (SFAs). The survey was sent via email to 18,790 SFAs, including all public, private, and charter SFAs operating the National School Lunch Program during School Year (SY) 2023-24. The questionnaire collected data on supply chain-related challenges, their impacts on school meal operations, and strategies SFAs used to address them. The response rate for the survey was 71 percent.Processing methods and equipment usedThe survey for School Year (SY) 2023-24 was administered solely via the web. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. This process involved examining the data for logical errors. The study team linked the Survey III data to administrative data from the FNS-742 form and from the National Center of Education Statistics (NCES) Common Core of Data (CCD). Records from the CCD were used to construct a measure of urbanicity, which classifies the area in which schools are located. Survey weights were generated to correct for survey non-response and generate nationally representative estimates.Study date(s) and durationData collection occurred from January 29, 2024 to March 19, 2024. Questions asked about challenges and school meal operation costs prior to and during SY 2023-24.Study spatial scale (size of replicates and spatial scale of study area)Respondents to the survey included SFAs from all 50 States as well as American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and Washington, DC.Level of true replicationNoneSampling precision (within-replicate sampling or pseudoreplication)No sampling was involved in the collection of this data.Level of subsampling (number and repeat or within-replicate sampling)No sampling was involved in the collection of this data.Study design (before–after, control–impacts, time series, before–after-control–impacts)None – Non-experimentalDescription of any data manipulation, modeling, or statistical analysis undertakenEach entry in the dataset contains SFA-level responses to the questionnaire. This file includes information from only SFAs that clicked “Submit” on the questionnaire.In addition, the file contains weights created to produce national estimates for the SY 2023-24 Survey on Supply Chain Challenges and Student Participation.While responses are made available for individual SFAs, these SFAs have been de-identified. Information is not included about the SFA name, address, state, or any information for the individual who completed the questionnaire.Access to restricted data may be made available upon request. Restricted variables include: State identifier; answers to open-ended questions about experience with universal meals, experience with CEP, reasons for high food costs, reasons for high labor costs, reasons for changes in student participation, reasons for increasing/decreasing local food purchases, and other comments.Description of any gaps in the data or other limiting factorsThis is not a complete survey of all SFAs. While the survey was set to all SFAs, the response rate was 71 percent. Part of the reason for non-response was outdated contact information that FNS was not able to rectify for this survey. Of 18,790 SFAs, 1,262 (6.7% of SFAs contacted) had email addresses to which the study team was unable to deliver messages. Survey weights are included to adjust for this non-response bias and obtain nationally representative estimates.Outcome measurement methods and equipment usedNone

An area defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township. Metadata

This repository contains data and code used in:

Isaac Mpanga, Russel Trondstad, Jessica Guo, David LeBauer, and John Omololu, 2021. On-farm land management strategies and production challenges in United States Organic Agricultural Systems. Current Research in Environmental Sustainability.

It provides USDA Surveys of Agricultural Production from 2008-2019 to investigate state and national trends by state in organic farm area, number, and sales, as well to evaluate national trends in on-farm land-use practices and challenges facing US organic production.

It also includes code used to transform, visualize, and analyze the data, and derived data products - notably organic farm area and sales with values imputed to correct for redacted state level measures.

Note: This is a large dataset. To download, go to ArcGIS Open Data Set and click the download button, and under additional resources select the shapefile or geodatabase option. A land survey point from a GCDB LX file, survey plat, or captured from a CFF land net coverage. Includes points generated by calculating an aliquot breakdown of a section.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService CSV Shapefile GeoJSON KML Geodatabase Download Shapefile Download For complete information, please visit https://data.gov.

With the passage of the Agricultural Improvement Act of 2018 (known as the 2018 Farm Bill), states are now required to provide case management to all Supplemental Nutrition Assistance Program (SNAP) Employment and Training (E&T) program participants. Although some states have provided case management as part of their SNAP E&T programs for many years, others are now implementing it for the first time or enhancing their services in response to this requirement. States' case management and assessment practices have not been well documented.

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, 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 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.Individual Metadata [XML]

An area defined by the Public Lands Survey System grid that is referenced by its tier and range numbers, and is normally a rectangle approximately 6 miles on a side with boundaries conforming to meridians and parallels. Metadata