This layer is sourced from gisprpxy.itd.state.ma.us.

April 2022

Massachusetts Counties, based on Survey Towns. Contains the 14 county polygons and a detailed coastline. Published as a map service from MassGIS' ArcGIS Server platform.See full metadata

This map service contains boundaries for the following types of public school districts:Local School - administered by a city or town school committee.Regional Academic - administered by a regional school committee.Regional Vocational Technical - administered by a regional vocational school committee.Independent Vocational and County Agricultural - administered by a board of trustees.Independent Public, including Commonwealth Charter Schools and Horace Mann Charter SchoolsDistrict information as of December 2, 2014, was obtained from the Massachusetts Department of Elementary and Secondary Education (ESE).For full metadata see https://www.mass.gov/info-details/massgis-data-public-school-districtsMap service also available.

The 2015 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). Spatial data is georeferenced to the earth surface using the Transverse Mercator projected coordinate system and the North American Datum of 1983. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:6000.

Click on any of the layers below to learn more about these data. Data are either generated by the Martha's Vineyard Commission or another entity which has their data distributed by MassGIS.Other informative websites with more spatial data to peruse:Dukes County GIS GalleryDukes County GIS Data HubMassGIS Data LayersMassGIS Data HubMass MapperMassCZM Sea Level Rise and Coastal Flooding Viewer

Be certain to read the MassGIS methodology to fully understand how these areas are identified.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). Spatial data is georeferenced to the earth surface using the Wisconsin Transverse Mercator projected coordinate system and the North American Datum of 1983. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:6000.

Prior to upload to the AGOL cloud, the Martha's Vineyard Commission set a definition query to only include those parcels having an Assessor's Use Code of either 6*, 7*, or 8*.The parcel boundaries and info are the most recent available per MassGIS as of June 2019. For the most current assessing info, please contact the Town's Assessing Office.The parcel boundaries and attribute table conform to the State's Level 3 Parcel Data Standard. See MassGIS for full details.See the MA Property Types Classification Code for a full explanation of each code.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Crosswalk numbers for the city of Boston. Generated in July 2008 from original maps dated 1951-1962 and related sketches. Placed using centerlines from Water and Sewer as well as block defintions. Shapefiles for individual districts were merged into this one file but do not have an active connection. Some discrepency between centerlines and earlier maps was allowed, though obvious problems were marked in red. The legend is consistent between all districts, except for Roxbury where the map did not distinguish mid-block or school crosswalks.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).

The MassDEP Wetlands dataset comprises two ArcGIS geodatabase feature classes:The WETLANDSDEP_POLY layer contains polygon features delineating mapped wetland resource areas and attribute codes indicating wetland type.The WETLANDSDEP_ARC layer was generated from the polygon features and contains arc attribute coding based on the adjacent polygons as well as arcs defined as hydrologic connections.Together these statewide layers enhance and replace the original MassDEP wetlands layers, formerly known as DEP Wetlands (1:12,000). It should be noted that these layers provide a medium-scale representation of the wetland areas of the state and are for planning purposes only. Wetlands boundary determination for other purposes, such as the Wetlands Protection Act MA Act M.G.L. c. 131 or local bylaws must use the relevant procedures and criteria.The original MassDEP wetlands mapping project was based on the photo-interpretation of 1:12,000, stereo color-infrared (CIR) photography, captured between 1990 and 2000, and included field verification by the MassDEP Wetlands Conservancy Program (WCP). In 2007 the MassDEP WCP began a statewide effort to assess and where necessary update the original wetlands data. The MassDEP WCP used ESRI ArcGIS Desktop software, assisted by the PurVIEW Stereo Viewing extension, to evaluate and update the original wetlands features based on photo-interpretation of 0.5m, (1:5,000) digital stereo CIR imagery statewide, captured in April 2005. No field verification was conducted on this updated 2005 wetlands data.The 2005 WETLANDSDEP_POLY layer includes polygon features that distinguish it from its predecessor by overall changes in size and shape. In addition, new polygons have been created and original ones deleted. Many of the polygons, however, remain the same as in the original layer. All changes have been made according to the techniques described below. For the purpose of cartographic continuity, a small number of coastal polygons outside the state boundary where added based on data provided by the United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA).The 2005 WETLANDSDEP_ARC layer was generated to support map display and was designed to cartographically enhance the rendering of wetland features on a base map. Arc features in this layer were generated from the wetland polygons and coding (ARC_CODE) was assigned based on the adjacent polygon types. Hydrologic connection features (ARC_CODE = 7) were then added. Where delineated, these arc features indicate an observed hydrologic connection to or between wetland polygons. Although efforts were made to be comprehensive and thorough in mapping hydrologic connections, due to the limitations of aerial photo-interpretation some areas may have been missed.The types of updates made to the original wetland features include alteration, movement/realignment and reclassification. In some cases original wetland areas have been deleted and new areas have been added. Updates to original wetland features resulted from the following factors: changes in the natural environment due to human activity or natural causes; advances in the field of remote sensing, allowing for more refined mapping.Edit changes to the original wetland data include:Addition of new wetland and hydrologic connection featuresAppending (expansion or realignment) of existing (original) wetland and hydrologic connection featuresReclassification of wetlands features, due to change in wetlands environment from the original classificationMovement (or shifting) of original wetland features to better match the source imageryDeletion of original wetland or hydrologic connection features due to changes in wetlands environment or inconsistency with mapping criteria.Please note that although efforts were made to be comprehensive and thorough in the evaluation and mapping of statewide wetland resources some areas of the state may have been missed. Many of the wetland and hydrologic connection features remain the same as in the original data. The polygon attribute SOURCE_SCALE may be used to identify areas that have been altered from the original wetlands. The SOURCE_SCALE code 5000 indicates an updated wetland area. The SOURCE_SCALE code 12000 indicates an unaltered, original wetland polygon.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

Geospatial data about Worcester County, Massachusetts Contours. Export to CAD, GIS, PDF, CSV and access via API.

U.S. Census Bureau QuickFacts statistics for Suffolk County, Massachusetts. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

no abstract provided

Find Massachusetts health data by community, county, and region, including population demographics. Build custom data reports with over 100 health and social determinants of health data indicators and explore over 28,000 current and historical data layers in the map room.

These data represent a digital form of the geologic map of Cape Cod and the islands.