This new atlas was co-developed by the Ministry of Agriculture and Forestry (MAF) and the Centre for Development and Environment (CDE) of the University of Bern. It combines statistical data from the last two agriculture censuses with detailed geographic information to presents a wealth of new sector-specific information on a large set of highly detailed thematic maps. Not only does the atlas provide new insights into the current socio-economic and agricultural patterns in the country: It also reveals the dynamics over space and time within the decade-long inter-census period, at village-level and for the whole of the Lao PDRThese Guidelines are intended to provide guidance to the policy, planning and technical support services of government, but the requirements of these different end - user groups are diverse. Consequently a scoping analysis was undertaken of the issues and responses of these end-user groups so the Guidelines could be framed to meet their requirements.

View the diversity of challenges and opportunities across America's counties within different types of rural regions and communities. Get statistics on people, jobs, and agriculture.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: Data file GIS API Services Interactive map Zip of CSV files For complete information, please visit https://data.gov.

The Agricultural Land Resource Atlas of Alberta is a collection of agricultural resource maps developed following the completion of a scan of environmental issues facing agriculture in Alberta. The maps were prepared as part of this process, or were added to the collection because of their potential value to Alberta's agricultural community. The maps were recognized for their value to people involved in developing environmental farm plans who could use resource and environmental information on a broad scale.

Ruminant ivestock distribution Africa. Data from CCAFS/ILRI/ERGO/FAO/ULB & World Bank. Map published in Atlas of African Agriculture Research & Development (K. Sebastian (Ed.) 2014). p.26-27 Ruminant Livestock. Contributors: T Robinson, W Wint, G Conchedda, G Cinardi & M Gilbert.For more information: http://agatlas.org/contents/ruminant-livestock/Robinson T., Wint W., Conchedda G., Cinardi G., and Gilbert M. (2014). Ruminant Livestock. In K. Sebastian (Ed.), Atlas of African Agriculture Research & Development. IFPRI. Washington, D.C.

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

This coverage contains estimates of land in agricultural production in counties in the conterminous United States as reported in the 1987 Census of Agriculture (U.S. Department of Commerce, 1989a). Land in agriculture data are reported as either a number (for example, number of Farms), acres, or as a percentage of county area. Land in agriculture estimates were generated from surveys of all farms where $1,000 or more of agricultural products were sold, or normally would have been sold, during the census year. Most of the attributes summarized represent 1987 data, but some information for the 1982 Census of Agriculture also was included. The polygons representing county boundaries in the conterminous United States, as well as lakes, estuaries, and other nonland-area features were derived from the Digital Line Graph (DLG) files representing the 1:2,000,000-scale map in the National Atlas of the United States (1970). Agricultural land Census of Agriculture Counties United States

Abstract The Catchment Scale Land Use of Australia – Update December 2023 dataset is the national compilation of catchment scale land use data available for Australia (CLUM), as of December 2023. It replaces the Catchment Scale Land Use of Australia – Update December 2020. It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. The CLUM data shows a single dominant land use for a given area, based on the primary management objective of the land manager (as identified by state and territory agencies). Land use is classified according to the Australian Land Use and Management Classification version 8. It has been compiled from vector land use datasets collected as part of state and territory mapping programs and other authoritative sources, through the Australian Collaborative Land Use and Management Program. Catchment scale land use data was produced by combining land tenure and other types of land use information including, fine-scale satellite data, ancillary datasets, and information collected in the field. The date of mapping (2008 to 2023) and scale of mapping (1:5,000 to 1:250,000) vary, reflecting the source data, capture date and scale. Date and scale of mapping are provided in supporting datasets.

Currency Date modified: December 2023 Publication Date: June 2024 Modification frequency: As needed (approximately annual) Data Extent Coordinate reference: WGS84 / Mercator Auxiliary Sphere Spatial Extent North: -9.995 South: -44.005 East: 154.004 West: 112.505 Source information Data, Metadata, Maps and Interactive views are available from Catchment Scale Land Use of Australia - Update 2023 Catchment Scale Land Use of Australia - Update 2023 – Descriptive metadata The data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license. Lineage statement This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). 2023 updates include more current data and/or reclassification of existing data. The following areas have updated data since the December 2020 version:

New South Wales (2017 v1.5 from v1.2). Northern Territory (2022 from 2020). Tasmania (2021 from 2019). Victoria (2021 from 2017). Data were also added from the Great Barrier Reef Natural Resource Management (NRM) regions in Queensland (2021 from a variety of dates 2009 to 2017). the Australian Tree Crops. Australian Protected Cropping Structures and Queensland Soybean Crops maps as downloaded on 30 November 2023. The capital city of Adelaide was updated using 2021 mesh block information from the Australian Bureau of Statistics. Minor reclassifications were made for Western Australia and mining area within mining tenements more accurately delineated in South Australia.

Links to land use mapping datasets and metadata are available at the ACLUMP data download page at agriculture.gov.au. State and territory vector catchment scale land use data were produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field, as outlined in 'Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition' (ABARES 2011). The Northern Territory, Queensland, South Australia, Tasmania, Victoria and Western Australia were mapped to version 8 of the ALUM classification (‘The Australian Land Use and Management Classification Version 8’, ABARES 2016). The Australian Capital Territory was mapped to version 7 of the ALUM classification and converted to version 8 using a look-up table based on Appendix 1 of ABARES (2016). Purpose for which the material was obtained: This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). Do not use this data to:

Derive national statistics. The Land use of Australia data series should be used for this purpose. Calculate land use change. The Land use of Australia data series should be used for this purpose.

It is not possible to calculate land use change statistics between annual CLUM national compilations as not all regions are updated each year; land use mapping methodologies, precision, accuracy and source data and satellite imagery have improved over the years; and the land use classification has changed over time. It is only possible to calculate change when earlier land use datasets have been revised and corrected to ensure that changes detected are real change and not an artefact of the mapping process. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in October 2024 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster was created with RGB fields as a colour map with Geoprocessing tools in ArcPro. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in February 2025 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster dataset was created with RGB fields as a colour map with Geoprocessing tools in ArcPro, and the raster dataset was re-projected from 1994 Australia Albers to WGS 1984 Web Mercator (Auxiliary Sphere). Data dictionary

Field name DField description Code values

OID Internal feature number that uniquely identifies each row Integer

Service Pixel value (Date) The year for which land use was mapped in the vector data provided by state and territory agencies or others, Date Range: 2008 to 2023 Integer

Count Count of the number of raster cells in each class of VALUE Integer

Label Reflecting the Date of the source data ranges from 2008 to 2023 Text

Contact Department of Agriculture, Fisheries and Forestry (ABARES), info.ABARES@aff.gov.au

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows the land where data exists as: land in agricultural use, land not in agricultural use but capable of limited agriculture and non-agricultural land. The map uses 1971 data from Canada Land Inventory.

ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. The ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources.

Hydrological data range from 1950-2000, biological data range from 1998-2004 and were compiled in 2003-2004. Data are presented as GIS and associated files, with included MOSS and .PDF files for non-GIS users. Extensive documentation is included with the data.

Updates to these data were received as DVD in 2008, including the Northwest Arctic, Western Alaska, and North Slope and were archived at NCEI under accession number 0049913.

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.

This dataset comprises the Environmental Sensitivity Index (ESI) data for Northwest Arctic, Alaska. ESI data characterize estuarine environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. This dataset contains hydrology data.

The ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources.

This dataset comprises the Environmental Sensitivity Index (ESI) data for Northwest Arctic, Alaska. ESI data characterize estuarine environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. This dataset contains hydrology data.

The ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources.

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 winter 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 Winter 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 HarvestedProduction in BushelsIrrigated Area Harvested in AcresAdditionally attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.Additional information on wheat from the Census of Agriculture is available in the USDA Census of Agriculture 2017 - Wheat Production layer.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.

The United States Department of Agriculture publishes the Food Environment Atlas so researchers can study the interaction of access to healthy food options, demographic factors and economic indicators to inform policymakers.

Per the United States Department of Agriculture website, "The current version of the Food Environment Atlas has over 275 variables, including new indicators on access and proximity to a grocery store for sub populations; an indicator on the SNAP Combined Application Project for recipients of Supplemental Security Income (at the State level); and indicators on farmers' markets that report accepting credit cards or report selling baked and prepared food products. All of the data included in the Atlas are aggregated into an Excel spreadsheet for easy download. These data are from a variety of sources and cover varying years and geographic levels. The documentation for each version of the data provides complete information on definitions and data sources."

Some questions you might be able to answer include:

• What factors are correlated with food deserts?
• What kind of relationship exists between the price of food and the health of the population?
• Which communities are high risk for children in terms of access to healthy food?

Photo by NeONBRAND on Unsplash

The Swedish Environmental Protection Agency, together with the Swedish National Heritage Board and the Swedish Board of Agriculture, ordered processed data from the Agricultural Register from Statistics Sweden in something called Statistics Sweden-Atlas Agriculture. The work was part of the so-called LiM project, a follow-up and evaluation of the environmental effects of the 1990 food policy. The aim was to monitor and analyse changes in agriculture from the post-war period to the 1990s. All data are converted into the 1992 administrative breakdown in order to obtain comparability over time. The Handbook for Statistics Sweden-Atlas Agriculture contains a full description of all the constituent variables and also describes how Statistics Sweden has proceeded with conversions etc.

The Atlas Agricultural Statistics is a publication of official statistics showing georeferenced data from the 2010 and 2020 agricultural censuses and the 2016 agricultural structure survey in small-scale grid cells and river basin units

The service provides spatial information on the subject. Seat and competence of public institutions in the area of the Bavarian State Ministry of Food, Agriculture, Forestry and Tourism.

The 2015 Hawaii Statewide Agricultural Land Use Baseline layer was created to provide a snapshot of contemporary commercial agricultural land use activity in Hawaii. It is based upon an assemblage of geospatial datasets, primarily high-resolution WorldView-2 satellite imagery (2011-2013) used as a base layer for digitization. Additional datasets used in this work include GIS layers (‘Agriculture and Farming’, ‘Inland Water Resources’, and ‘Cadastral and Land Descriptions’) provided by the state of Hawaii, Office of Planning Statewide GIS Program and other data provided by major land owners and managers. Digitized crop locations and boundaries were verified through a combination of on-the-ground site visits, meetings and presentations of draft layers with agricultural stakeholders and landowners, solicitations through a publicly accessible online web mapping portal, and spot-checking using Google Earth™ and other high resolution imagery sources. In addition to the satellite imagery, County Real Property Tax and Agricultural Water Use data were also used to identify commercial farm operations. Data for both real property tax assessment and agricultural water use were collected from each county thatprovided their most recent records, generally from 2014-2015. Not all properties that receive County agricultural tax assessment rates or reduced water cost for agricultural uses were mapped due to the small scale of some of their operations. These data sources were used to verify mapped commercial farms and identify operations that might have been missed using the imagery alone.The 2015 Hawaii Statewide Agricultural Land Use Baseline layer represents our best efforts to capture the scale and diversity of commercial agricultural activity in Hawaii in 2015 and should be used for informational purposes only. For more information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/aglanduse_2015.pdf or contact the Hawaii Statewide GIS Program at gis@hawaii.gov.

The highly diversified agriculture practised in Quebec in the past has been gradually replaced by more specialized agricultural practices and large-scale production. These changes have resulted in the disappearance of a significant portion of the woodlands that formerly were part of the agricultural landscape of southern Quebec.

It is becoming increasingly clear that these woodlands performed a number of highly important ecological and agronomic functions within the larger ecosystem, while ensuring the survival of indigenous plant and animal species in the agricultural landscape. It follows that conserving the woodland islands that remain is of the utmost importance, particularly in the sectors of Quebec where agriculture has been practiced intensively in recent decades.

In recent years, the Canadian Wildlife Service of Environment Canada has responded to the challenge of maintaining biodiversity in agricultural ecosystems by developing a Conservation Atlas of Woodlands in the Agricultural Landscape, the primary purpose of which is to determine the status of woodlands and forest fragmentation in southern Quebec. The Atlas also reflects the knowledge acquired to date on the use of these habitats by birds (many species of which are highly vulnerable to landscape fragmentation) and, as such, will complement the information already available on the presence of animal and plant species and will serve as a decision-making tool for managers and conservation groups in the region.

Woodland polygons are derived from Landsat-TM5 satellite image classifications from 1993 and 1994, upon which the boundaries of regional county municipalities and the outlines of Quebec’s potential agriculture zone have been superimposed. RCM boundaries are derived from the administrative boundary file (FILA, updated 1996) of the Ministère des ressources naturelles du Québec, with a scale of 1: 250,000).

Attributes description is available here: \int.ec.gc.ca\sys\InGEO\GW\EC1142ProtAreas_AiresProt\Q C_SCF\Habitats\Boisé\Atlas_des_boisés

Polygons with a surface area of less than one hectare have been eliminated and contours have been smoothed out.

Contained within the 4th Edition (1974) of the Atlas of Canada is a map that shows the number of agricultural products by census division that are statistically significant in terms of value of sales from farms for 1961. The accompanying text is an overview of the Agriculture section of the 4th Edition National Atlas.