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.

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.

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.

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 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.

description: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2001 is used as non-agricultural training and validation data. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.; abstract: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2001 is used as non-agricultural training and validation data. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.

Abstract

For more than 150 years, the U.S. Department of Commerce, Bureau of the Census, conducted the census of agriculture. However, the 2002 Appropriations Act transferred the responsibility from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture for the U.S. Virgin Islands is the second census in the U.S. Virgin Islands conducted by NASS. The census of agriculture is taken to obtain agricultural statistics for each county, State (including territories and protectorates), and the Nation. The first U.S. agricultural census data were collected in 1840 as a part of the sixth decennial census. From 1840 to 1920, an agricultural census was taken as a part of each decennial census. Since 1920, a separate national agricultural census has been taken every 5 years. The 2007 census is the 14th census of agriculture of the U.S. Virgin Islands. The first, taken in 1920, was a special census authorized by the Secretary of Commerce. The next agriculture census was taken in 1930 in conjunction with the decennial census, a practice that continued every 10 years through 1960. The 1964 Census of Agriculture was the first quinquennial (5-year) census to be taken in the U.S. Virgin Islands. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data-reference year to coincide with the 1982 Economic Censuses covering manufacturing, mining, construction, retail trade, wholesale trade, service industries, and selected transportation activities. After 1982, the agriculture census reverted to a 5-year cycle. Data in this publication are for the calendar year 2007, and inventory data reflect what was on hand on December 31, 2007. This is the same reference period used in the 2002 census. Prior to the 2002 census, data was collected in the summer for the previous 12 months, with inventory items counted as what was on hand as of July 1 of the year the data collection was done.

Objectives: The census of agriculture is the leading source of statistics about the U.S. Virgin Islands’s agricultural production and the only source of consistent, comparable data at the island level. Census statistics are used to measure agricultural production and to identify trends in an ever changing agricultural sector. Many local programs use census data as a benchmark for designing and evaluating surveys. Private industry uses census statistics to provide a more effective production and distribution system for the agricultural community.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was a farm, defined as "any place from which USD 500 or more of agricultural products were produced and sold, or normally would had been sold, during the calendar year 2007". According to the census definition, a farm is essentially an operating unit, not an ownership tract. All land operated or managed by one person or partnership represents one farm. In the case of tenants, the land assigned to each tenant is considered a separate farm, even though the landlord may consider the entire landholding to be one unit rather than several separate units.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Method of Enumeration As in the previous censuses of the U.S. Virgin Islands, a direct enumeration procedure was used in the 2007 Census of Agriculture. Enumeration was based on a list of farm operators compiled by the U.S. Virgin Islands Department of Agriculture. This list was compiled with the help of the USDA Farm Services Agency located in St. Croix. The statistics in this report were collected from farm operators beginning in January of 2003. Each enumerator was assigned a list of individuals or farm operations from a master enumeration list. The enumerators contacted persons or operations on their list and completed a census report form for all farm operations. If the person on the list was not operating a farm, the enumerator recorded whether the land had been sold or rented to someone else and was still being used for agriculture. If land was sold or rented out, the enumerator got the name of the new operator and contacted that person to ensure that he or she was included in the census.

(b) Frame The census frame consisted of a list of farm operators compiled by the U.S. Virgin Islands DA. This list was compiled with the help of the USDA Farm Services Agency, located in St. Croix.

(c) Complete and/or sample enumeration methods The census was a complete enumeration of all farm operators registered in the list compiled by the United States of America in the CA 2007.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire (report form) for the CA 2007 was prepared by NASS, in cooperation with the DA of the U.S. Virgin Islands. Only one questionnaire was used for data collection covering topics on:

• Land owned
• Land use
• Irrigation
• Conservation programs and crop insurance
• Field crops
• Bananas, coffee, pineapples and plantain crops
• Hay and forage crops
• Nursery, Greenhouse, Floriculture, Sod and tree seedlings
• Vegetables and melons
• Hydroponic crops
• Fruit
• Root crops
• Cattle and calves
• Poultry
• Hogs and pigs
• Aquaculture
• Other animals and livestock products
• Value of sales
• Organic agriculture
• Federal and commonwealth agricultural program payments
• Income from farm-related sources
• Production expenses
• Farm labour
• Fertilizer and chemicals applied
• Market value of land and buildings
• Machinery, equipment and buildings
• Practices
• Type of organization
• Operator characteristics

The questionnaire of the 2007 CA covered 12 of the 16 core items' recommended for the WCA 2010 round.

Cleaning operations

DATA PROCESSING The processing of the 2007 Census of Agriculture for the U.S. Virgin Islands was done in St. Croix. Each report form was reviewed and coded prior to data keying. Report forms not meeting the census farm definition were voided. The remaining report forms were examined for clarity and completeness. Reporting errors in units of measures, illegible entries, and misplaced entries were corrected. After all the report forms had been reviewed and coded, the data were keyed and subjected to a thorough computer edit. The edit performed comprehensive checks for consistency and reasonableness, corrected erroneous or inconsistent data, supplied missing data based on similar farms, and assigned farm classification codes necessary for tabulating the data. All substantial changes to the data generated by the computer edits were reviewed and verified by analysts. Inconsistencies identified, but not corrected by the computer, were reviewed, corrected, and keyed to a correction file. The corrected data were then tabulated by the computer and reviewed by analysts. Prior to publication, tabulated totals were reviewed by analysts to identify inconsistencies and potential coverage problems. Comparisons were made with previous census data, as well as other available data. The computer system provided the capability to review up-to-date tallies of all selected data items for various sets of criteria which included, but were not limited to, geographic levels, farm types, and sales levels. Data were examined for each set of criteria and any inconsistencies or potential problems were then researched by examining individual data records contributing to the tabulated total. W hen necessary, data inconsistencies were resolved by making corrections to individual data records.

Sampling error estimates

The accuracy of these tabulated data is determined by the joint effects of the various nonsampling errors. No direct measures of these effects have been obtained; however, precautionary steps were taken in all phases of data collection, processing, and tabulation of the data in an effort to minimize the effects of nonsampling errors.

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

Note: This version supersedes version 1: https://doi.org/10.15482/USDA.ADC/1522654. In Fall of 2019 the USDA Food and Nutrition Service (FNS) conducted the third Farm to School Census. The 2019 Census was sent via email to 18,832 school food authorities (SFAs) including all public, private, and charter SFAs, as well as residential care institutions, participating in the National School Lunch Program. The questionnaire collected data on local food purchasing, edible school gardens, other farm to school activities and policies, and evidence of economic and nutritional impacts of participating in farm to school activities. A total of 12,634 SFAs completed usable responses to the 2019 Census. Version 2 adds the weight variable, “nrweight”, which is the Non-response weight. Processing methods and equipment used The 2019 Census 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, contacting SFAs and consulting official records to update some implausible values, and setting the remaining implausible values to missing. The study team linked the 2019 Census data to information 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. Study date(s) and duration Data collection occurred from September 9 to December 31, 2019. Questions asked about activities prior to, during and after SY 2018-19. The 2019 Census asked SFAs whether they currently participated in, had ever participated in or planned to participate in any of 30 farm to school activities. An SFA that participated in any of the defined activities in the 2018-19 school year received further questions. 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 replication Unknown Sampling 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-experimental Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains SFA-level responses to the Census questionnaire for SFAs that responded. This file includes information from only SFAs that clicked “Submit” on the questionnaire. (The dataset used to create the 2019 Farm to School Census Report includes additional SFAs that answered enough questions for their response to be considered usable.) In addition, the file contains constructed variables used for analytic purposes. The file does not include weights created to produce national estimates for the 2019 Farm to School Census Report. The dataset identified SFAs, but to protect individual privacy the file does not include any information for the individual who completed the questionnaire. Description of any gaps in the data or other limiting factors See the full 2019 Farm to School Census Report [https://www.fns.usda.gov/cfs/farm-school-census-and-comprehensive-review] for a detailed explanation of the study’s limitations. Outcome measurement methods and equipment used None Resources in this dataset:Resource Title: 2019 Farm to School Codebook with Weights. File Name: Codebook_Update_02SEP21.xlsxResource Description: 2019 Farm to School Codebook with WeightsResource Title: 2019 Farm to School Data with Weights CSV. File Name: census2019_public_use_with_weight.csvResource Description: 2019 Farm to School Data with Weights CSVResource Title: 2019 Farm to School Data with Weights SAS R Stata and SPSS Datasets. File Name: Farm_to_School_Data_AgDataCommons_SAS_SPSS_R_STATA_with_weight.zipResource Description: 2019 Farm to School Data with Weights SAS R Stata and SPSS Datasets

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.

The Agricultural Resource Management Survey (ARMS) is a dataset created by the U.S. Department of Agriculture (USDA), jointly administered by the Economic Research Service (ERS) and the National Agricultural Statistics Service (NASS). It serves as the primary source of information on farm production practices, resource use, financial conditions, and the economic well-being of U.S. farm households. The dataset collects detailed, farm-level data through annual surveys, covering topics such as crop production, input costs, income, and sustainability practices. Its purpose is to inform USDA, Congress, and industry stakeholders about agricultural trends, enabling evidence-based policy and program decisions. For example, ARMS data supports evaluations of farm subsidies, environmental programs, and market dynamics. Key features include its comprehensive scope, combining financial and operational metrics, and its representative sampling of U.S. farms and ranches. Unique aspects include the use of advanced statistical methods like the delete-a-group jackknife for variance estimation and the availability of data via an API and bulk files for researchers. ARMS is also critical for developing models like unit process data for crop production, enhancing agricultural research and sustainability studies. (Word count: 198)

"Agricultural Chemical Usage, Field Crops Summary" contains state and U.S. fertilizer and pesticide use data for corn, cotton, peanuts, rice, sorghum, soybeans, wheat, fall potatoes. Includes pesticide use by active ingredient, application rates, and acres treated.

  Collection Organization: ERS and NASS

  Collection Methodology: The information presented is the result
  of a sample survey conducted for the crop year (end of harvest
  for previous crop through harvest of current crop). A random
  sample of fields was selected with probability proportional to
  size, using information, obtained earlier in the year, from two
  surveys of farm operators. Personal interviews were used to
  obtain the information. Chemical data were collected at the
  product level and converted to active ingredient for
  summarization.

  Collection Frequency: Annual survey.

  Update Characteristics: Dataset not updated.

  STATISTICAL INFORMATION:

  The data reside in one ASCII text file.
  LANGUAGE:

  English
  ACCESS/AVAILABILITY:

  Data Center: National Agricultural Statistics Service
  Dissemination Media: Diskette, Internet home page
  File Format: ASCII delimited
  Access Instructions: Call NASS at 1-800-999-6779 for historical
  series data available on diskette. For historical series data
  available online, connect to the Internet home page at Cornell
  University.

  Or connect at the NASS Internet home page.

        URL: 'http://www.nass.usda.gov/index.asp'

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

The statistical information in the "Financial Characteristics of Horticultural Farms" dataset provides an overview of farm business financial performance (such as income statements, balance sheets, and financial ratios) for 1987 through 1991 as sources from USDA's Annual Farm Costs and Return Survey (FCRS). These FCRS data are "industry-level" estimates for all growers of nonedible horticultural crops and, with the exception of cut Christmas tree farms, data are not available for subsectors such as nursery plant farms and cut flower farms. However, detailed financial data are available by year, by economic classes, and by region.

Collection Organization: Economic Research Service.

Collection Methodology: USDA Annual Farm Costs and Return Survey, Census of Agriculture.

Collection Frequency: Annually.

Update Characteristics: Updated in its entirety.

STATISTICAL INFORMATION:

The data reside in 76 LOTUS 1-2-3 worksheet files, 8 Lotus Freelance Graphics files, and one ASCII text file. LANGUAGE:

English ACCESS/AVAILABILITY:

Data Center: USDA Economic Research Service Dissemination Media: Diskette, Internet gopher, Internet home page File Format: ASCII, Lotus/dBase Access Instructions: Call NASS at 1-800-999-6779 for historical series data available on diskette. For historical series data available online, connect to the Internet home page at Cornell University.

    URL: 'http://usda.mannlib.cornell.edu/MannUsda/homepage.do'

Access to the data or reports may be achieved through the ERS-NASS information system:

    WWW:

'http://usda.mannlib.cornell.edu/MannUsda/homepage.do'

For subscription direct to an e-mail address, send an e-mail message to:

     usda-reports@usda.mannlib..cornell.edu

Type the word "lists" (without quotes) in the body of the message.

Description of the experiment setting: location, influential climatic conditions, controlled conditions (e.g. temperature, light cycle)In Fall of 2023 the USDA Food and Nutrition Service (FNS) conducted the fourth Farm to School Census. The 2023 Census was sent via email to 18,833 school food authorities (SFAs) including all public, private, and charter SFAs, as well as residential care institutions, participating in the National School Lunch Program. The questionnaire collected data on local food purchasing, edible school gardens, other farm to school activities and policies, and outcomes and challenges of participating in farm to school activities. A total of 12,559 SFAs submitted a response to the 2023 Census.Processing methods and equipment usedThe 2023 Census 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 and removing implausible values. The study team linked the 2023 Census data to information 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.Study date(s) and durationData collection occurred from October 2, 2023 to January 7, 2024. Questions asked about activities prior to, during and after SY 2022-23. The 2023 Census asked SFAs whether they currently participated in, had ever participated in or planned to participate in any of 32 farm to school activities. Based on those answers, SFAs received a defined set of further questions.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 replicationUnknownSampling 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 Census questionnaire for SFAs that responded. This file includes information from only SFAs that clicked “Submit” on the questionnaire. (The dataset used to create the 2023 Farm to School Census Report includes additional SFAs that answered enough questions for their response to be considered usable.)In addition, the file contains constructed variables used for analytic purposes. The file does not include weights created to produce national estimates for the 2023 Farm to School Census Report.The dataset identified SFAs, but to protect individual privacy the file does not include any information for the individual who completed the questionnaire. All responses to open-ended questions (i.e., containing user-supplied text) were also removed to protect privacy.Description of any gaps in the data or other limiting factorsSee the full 2023 Farm to School Census Report [https://www.fns.usda.gov/research/f2s/2023-census] for a detailed explanation of the study’s limitations.Outcome measurement methods and equipment usedNone

description:

The USDA-NASS 2000 North Dakota Cropland Data Layer is a raster, geo-referenced, categorized land cover data layer produced using satellite imagery from the Thematic Mapper (TM) instrument on Landsat 5 and the Enhanced Thematic Mapper (ETM+) on Landsat 7. The imagery was collected between the dates of April 23, 2000 and September 15, 2000. The approximate scale is 1:100,000 with a ground resolution of 30 meters by 30 meters. The North Dakota data layer is aggregated to 17 standardized categories for display purposes with the emphasis being agricultural land cover. This is part of an annual series in which several states are categorized annually based on the extensive field observations collected during the annual NASS June Agricultural Survey. However, no farmer reported data is included or derivable on the Cropland Data Layer CD-ROM.

Constraints:
There are NO copyright restrictions with either the NASS Cropland categorized imagery or ESRI's ArcExplorer software included on the CD-Rom. The NASS Cropland categorized imagery is considered public domain and FREE to redistribute. However, NASS would appreciate acknowledgment or credit for the usage of our categorized imagery. Users of our Cropland Data Layer (CDL) and associated raster and vector data files are solely responsible for interpretations made from these products. The CDL is provided "as is". USDA-NASS does not warrant results you may obtain by using the Cropland Data Layer. Feel free to contact our staff at (HQ_RD_OD@nass.usda.gov) if technical questions arise in the use of our Cropland Data Layer. NASS does provide considerable metadata on the CDL in the Frequently Asked Questions (FAQ's) section on this CDL website, and on the ordered CD's. Also, there are substantial statistical performance measures by Analysis District within a State on the Landsat data categorization accuracies for each CD for each year. Not to be used for navigation, for informational purposes only. See full disclaimer for more information.

The USDA-NASS 2000 North Dakota Cropland Data Layer is a raster, geo-referenced, categorized land cover data layer produced using satellite imagery from the Thematic Mapper (TM) instrument on Landsat 5 and the Enhanced Thematic Mapper (ETM+) on Landsat 7. The imagery was collected between the dates of April 23, 2000 and September 15, 2000. The approximate scale is 1:100,000 with a ground resolution of 30 meters by 30 meters. The North Dakota data layer is aggregated to 17 standardized categories for display purposes with the emphasis being agricultural land cover. This is part of an annual series in which several states are categorized annually based on the extensive field observations collected during the annual NASS June Agricultural Survey. However, no farmer reported data is included or derivable on the Cropland Data Layer CD-ROM.

Constraints:
There are NO copyright restrictions with either the NASS Cropland categorized imagery or ESRI's ArcExplorer software included on the CD-Rom. The NASS Cropland categorized imagery is considered public domain and FREE to redistribute. However, NASS would appreciate acknowledgment or credit for the usage of our categorized imagery. Users of our Cropland Data Layer (CDL) and associated raster and vector data files are solely responsible for interpretations made from these products. The CDL is provided "as is". USDA-NASS does not warrant results you may obtain by using the Cropland Data Layer. Feel free to contact our staff at (HQ_RD_OD@nass.usda.gov) if technical questions arise in the use of our Cropland Data Layer. NASS does provide considerable metadata on the CDL in the Frequently Asked Questions (FAQ's) section on this CDL website, and on the ordered CD's. Also, there are substantial statistical performance measures by Analysis District within a State on the Landsat data categorization accuracies for each CD for each year. Not to be used for navigation, for informational purposes only. See full disclaimer for more information.

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.

The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2009 CDL has a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Database 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2001 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer. The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products. please visit this internet site http://www.nass.usda.gov/research/Cropland/metadata/meta.htm to view the original metadata file.

The USDA-NASS 1997 North Dakota Cropland Data Layer is a raster, geo-referenced, categorized land cover data layer produced using satellite imagery from the Thematic Mapper (TM) instrument on Landsat 5, and the Enhanced Thematic Mapper (ETM+) on Landsat 7. The imagery was collected between the dates of June 10, 1997 and September 25, 1997. The approximate scale is 1:100,000 with a ground resolution of 30 meters by 30 meters. The North Dakota data layer is aggregated to 16 standardized categories for display purposes with the emphasis being agricultural land cover. This is part of an annual series in which several states are categorized annually based on the extensive field observations collected during the annual NASS June Agricultural Survey. However, no farmer reported data is included or derivable on the Cropland Data Layer CD-ROM.

Constraints:
Users of our Cropland Data Layer (CDL) and associated raster and vector data files are solely responsible for interpretations made from these products. The CDL is provided "as is". USDA-NASS does not warrant results you may obtain by using the Cropland Data Layer. Feel free to contact our staff at (HQ_RD_OD@nass.usda.gov) if technical questions arise in the use of our Cropland Data Layer. NASS does provide considerable metadata and substantial statistical performance measures in the Frequently Asked Questions (FAQ's) section on the CDL website and on the CD-ROM and/or DVD. Not to be used for navigation, for informational purposes only. See full disclaimer for more information.

The annual Agricultural Resource Management Survey (ARMS) is USDA's primary source of information on the financial condition, production practices, and resource use of America's farm businesses and the economic well-being of America's farm households. ARMS data are essential to USDA, congressional, administration, and industry decision makers when weighing alternative policies and programs that touch the farm sector or affect farm families.

The ERS content and data APIs (including our pre-made widgets for embedding charts) are currently out of service while we redesign our site. Check back here for updates--we'll keep you informed as to the progress. Contact us at webadmin@ers.usda.gov with questions.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: Query tool - Farm structure and finance Query tool - Crop production practices For complete information, please visit https://data.gov.