Application showing SNAP clients by Municipality in Massachusetts. Data provided by the Department of Transitional Assistance as of September 2025. Population data sourced from the 2020 US Census.

Note: The Food Environment Atlas contains ERS's most recent and reliable data on food assistance programs, including participants in the SNAP Program. The Supplemental Nutrition Assistance Program (SNAP) Data System is no longer being updated due to inconsistencies and reliability issues in the source data. The Supplemental Nutrition Assistance Program (SNAP) Data System provides time-series data on State and county-level estimates of SNAP participation and benefit levels, combined with area estimates of total population and the number of persons in poverty.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: Interactive map GIS API Services Data file For complete information, please visit https://data.gov.

Feature layer generated from running the Dissolve Boundaries solution.

SNAP Retail Locations https://services1.arcgis.com/RLQu0rK7h4kbsBq5/arcgis/rest/services/Store_Locations/FeatureServer/0

{"definition": "2000 average monthly SNAP benefit per participant", "availableYears": "2000", "name": "2000 average monthly SNAP benefit per participant", "units": "Dollars/participant", "shortName": "AMB_PAR00", "geographicLevel": "County", "dataSources": "Estimates of total annual benefits issued by area are provided by the Regional Economic Information System, Bureau of Economic Analysis of the U.S. Department of Commerce."}

© Dollars/participant This layer is a component of ERS SNAP Data System.

This map service contains maps and data relevant to SNAP (Supplemental Nutrition Assistance Program) participation and benefits

© Detailed documentation on data sources used in the ERS SNAP Data System map services is available here: http://www.ers.usda.gov/data-products/supplemental-nutrition-assistance-program-(snap)-data-system/documentation.aspx

Beginning in 2015, the Public Service Communication Board, VITA Integrated Services Program staff, and staffs from public safety answering points (PSAPs) have been planning the deployment of Next Generation 9-1-1 (NG911) for the Commonwealth. Transitioning from the legacy telecommunication network will provide numerous benefits and flexibility looking towards the future. As the emergency services internet protocol network (ESInet) is fully deployed, geospatial call routing will use geographic information system (GIS) data provisioned by authoritative sources. This process includes compiling mutually agreed to available Provisioning Boundary Line segments received and processed by VITA ISP. Segments are connected by Provisioning Boundary Junctions. Road Centerline Snap to Points are created when an existing road centerline feature crosses an agreed-to provisioning boundary and are provided as a feature service https://vginmaps.vdem.virginia.gov/arcgis/rest/services/NG911/NG911_VA_StatePlaneSouth_NAD83_RCLSnapToPoint/FeatureServer in Virginia State Plane South. Guidance on connecting to feature services is available here: https://vginmaps.vdem.virginia.gov/download/ng911/Working_with_VGIN_Feature_Services.pdf. Data is believed to be current for its intended purpose. Additional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.Data is provided as is. All warranties regarding the accuracy of the data and any representation or inferences derived there from are hereby expressly disclaimed.

National Hydrography Dataset - for snapping diversions and other riverine features. SEO stream names - for referencing proper water sources. SEO Districts - Hydrographer districts for assigning a unique ID (WDOSTRID) on modeling projects. Public Land Survey System (PLSS)

Food stores that are certified to accept Supplemental Nutrition Assistance Program (SNAP - previously know as food stamps) Electronic Benefit Transfer (EBT) payments in Maryland.Data source: United States Department of Agriculture, Food and Nutrition ServiceDate: 2020

This dataset was updated May, 2025.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes:* Clipping input datasets to the California boundary* Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc)* Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California.* Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only.* Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs)* In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD* As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset. Data Sources:* GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf* US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore* Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases* Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov* Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.html Data Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.25_1: The CPAD Input dataset was amended to merge large gaps in certain areas of the state known to be erroneous, such as Yosemite National Park, and to eliminate overlaps from the original input. The FWS input dataset was updated in February of 2025, and the DOD input dataset was updated in October of 2024. The BIA input dataset was the same as was used for the previous ownership version.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.

The Sustainable Community Program focuses on creating healthy, livable, connected, and resilient neighbourhoods - both new and existing. Sustainable Neighbourhood Action Plans (SNAPs) are partnership initiatives between the City of Brampton, TRCA, CVC, and Region of Peel. SNAPs focus on environmental improvements and urban renewal of existing neighbourhoods, and promote widespread adoption of sustainable technologies, practices and lifestyle in the community. Brampton currently has two SNAPs, the County Court SNAP and the Fletchers Creek SNAP.Sustainable neighbourhood action plan areas delineate locations where special programs are offered to residents to upgrade their homes to make them energy/water efficient; special attention is made to improving the function of infrastructure and to promote sustainable habits.For more information, navigate to the City of Brampton website for this program.

This data set contains all Virginia Railway Express (VRE) stations in Virginia. The data set was originally obtained from the Metro Washington Council of Governments (MWCOG) GIS data clearinghouse and snapped to the Fairfax County railroad data set using 2002 aerial photography as a background. This data set was created to display all VRE stations in Virginia only and can be used in conjunction with the railroad data set.

This is a points data set of the location of urban waste water emission points, at the estimated point at which the emission joins the surface water network.

GIS-datasets for the Street networks of Stockholm, Gothenburg and Eskilstuna produced as part of the Spatial Morphology Lab (SMoL). The goal of the SMoL project is to develop a strong theory and methodology for urban planning & design research with an analytical approach. Three frequently recurring variables of spatial urban form are studied that together quite well capture and describe the central characteristics and qualities of the built environment: density, diversity and proximity. The first measure describes how intensive a place can be used depending on how much built up area is found there. The second measure captures how differentiated the use of a place can be depending on the division in smaller units such as plots. The third measure describes how accessible a place is depending on how it relates with other places. Empirical studies have shown strong links between these metrics and people's use of cities such as pedestrian movement patterns. To support this goal, a central objective of the project is the establishment of an international platform of GIS data models for comparative studies in spatial urban form comprising three European capitals: London in the UK, Amsterdam in the Netherlands and Stockholm in Sweden, as well as two additional Swedish cities of smaller size than Stockholm: Gothenburg and Eskilstuna. The result of the project is a GIS database for the five cities covering the three basic layers of urban form: street network (motorised and non-motorised), buildings and plots systems. The data is shared via SND to create a research infrastructure that is open to new study initiatives. The datasets for Amsterdam will also be uploaded to SND. The datasets of London cannot be uploaded because of licensing restrictions. The street network GIS-maps include motorised and non-motorised networks. The motorised networks exclude all streets that are pedestrian-only and were cars are excluded. The network layers are based on the Swedish national road database, NVDB (Nationell Vägdatabas), downloaded from Trafikverket (https://lastkajen.trafikverket.se, date of download 15-5-2016, last update 8-11-2015). The original road-centre-line maps of all cities were edited based on the same basic representational principles and were converted into line-segment maps, using the following software: FME, Mapinfo professional and PST (Place Syntax Tool). The coordinate system is SWEREF99TM. In the final line-segment maps (GIS-layers) all roads are represented with one line irrespectively of the number of lanes, except from Motorways and Highways which are represented with two lines, one for each direction, again irrespectively of the number of lanes. We followed the same editing and generalizing procedure for all maps aiming to remove errors and to increase comparability between networks. This process included removing duplicate and isolated lines, snapping and generalizing. The snapping threshold used was 2m (end points closer than 2m were snapped together). The generalizing threshold used was 1m (successive line segments with angular deviation less than 1m were merged into one). In the final editing step, all road polylines were segmented to their constituting line-segments. The aim was to create appropriate line-segment maps to be analysed using Angular Segment Analysis, a network centrality analysis method introduced in Space Syntax. All network layers are complemented with an “Unlink points” layer; a GIS point layer with the locations of all non-level intersections, such as overpasses and underpasses, bridges, tunnels, flyovers and the like. The Unlink point layer is necessary to conduct network analysis that takes into account the non-planarity of the street network, using such software as PST (Place Syntax Tool).

{"units": "Classification"}

The Supplemental Nutrition Assistance Program (SNAP) offers nutrition assistance to millions of eligible, low-income individuals and families and provides economic benefits to communities. SNAP is the largest program in the domestic hunger safety net.To be eligible as a SNAP retailer, store(s) must sell food for home preparation and consumption and meets additional criteria regarding the sale of staple foods. For technical assistance, contact the Florida's Roadmap to Healthy Living Administrator

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.

This political boundary layer is the most accurate representing the city and town boundaries in the Commonwealth of Massachusetts.This datalayer has been created from latitude and longitude coordinates found in the 68-volume Harbor and Lands Commission Town Boundary Atlas. This Atlas series, and updates since it was published, describes the legal boundary for each of the 351 municipalities in Massachusetts.
These coordinates were recorded from surveys of the location of each boundary marker around the periphery of each community. Each survey was tied into higher order monumented survey control points. The Atlases also include detailed descriptions of each community's boundary and location maps for each of the original boundary marker locations. The original surveys were conducted in the 1890s. The Atlas series was published in the early 1900s and has since been updated by the Survey Section of the Massachusetts Highway Department with changes as they are approved by the legislature.MassGIS staff collaborated closely with staff from the Survey Section during the development of this data layer. MassGIS staff keyed the coordinates into a database; that data entry was double-checked by staff from the Survey Section. Staff from the Survey Section then converted the latitude/longitude coordinates to the NAD83 datum and also created a version of the coordinates in state plane coordinates with units of meters. MassGIS used the state plane coordinates to "generate" points in ArcGIS. Boundary arcs from the existing USGS-derived municipal boundary data layer were then snapped to the survey-derived points. The differences between the municipal boundary arcs digitized from those on the USGS quads and those created by snapping to the survey-derived coordinates are typically plus or minus 12 feet, although these differences are sometimes less and sometimes more. Some municipal boundary arcs (about 15% of the total) follow the edge of a road or rail right-of-way or a stream or river channel. In these cases, the new boundary arcs were "heads up" digitized based on features visible on the statewide 1:5,000 color orthos from imagery flown in 2001. For communities with a coastal boundary, MassGIS collaborated with the Massachusetts Water Resources Authority and the Department of Environmental Protection to complete a 1:12,000 scale coastline.The boundaries are included in Esri's World Topographic Map through participation in its Community Maps program.City/Town names' labels are included in this service.(This service was published from a map document using the Web Mercator projection for the data frame.)For full metadata please see https://www.mass.gov/info-details/massgis-data-municipalities

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.

Last update: February 3, 2022 (minor geometry cleanup: snapping, remove topology slivers, etc.)This dataset includes the political districts used for the Utah State Legislature. Utah House Districts 2022 to 2032 will be used for election purposes beginning January 1, 2022. Elected officials began representing these districts in January 2023. These boundaries supersede the State House Districts that were used in 2012-2021. Statewide Political District Boundaries are drawn by the Utah Legislature and adopted into state law as part of the decennial redistricting process that began in 2021. These districts represent the Utah House Districts, as per the Census Block Assignment file, enrolled with HB2005.For information and downloads on all political districts check UGRC data page https://gis.utah.gov/data/political/2022-2032-house-senate-congressional-districts/

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.