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.

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 http://www.mass.gov/itd/townsurvey.

The political boundary datalayer is a polygon representation of town boundaries created from arcs developed from survey coordinates extracted from the 68-volume Harbor and Lands Commission Town Boundary Atlas for the 351 communities (cities and towns) in Massachusetts. The Atlas was published in the early 1900's and is maintained by the Survey Section of Massachusetts Highway Department. For communities with a coastal boundary, MassGIS has collaborated with Massachusetts Water Resources Authority and the Department of Environmental Protection to complete a 1:12000 scale coastline. The boundary for the coastline was defined as being the upland side of tidal flats and rocky inter-tidal zones. Note that the 351 communities are the official municipal names, not including "villages" or other sections of towns.

© Massachusetts Highway Survey Section, MassGIS This layer is sourced from gisprpxy.itd.state.ma.us.

This map service from MassGIS displays the 26 Massachusetts Gateway Cities, municipalities with:population greater than 35,000 and less than 250,000;median household income below the state average;and rate of educational attainment of a bachelor’s degree or above that is below the state average.Read more about Gateway CitiesMap service also available.

This map service displays the year in which cities and towns in Massachusetts were first settled by Europeans. The data were gathered by the Secretary of the Commonwealth of Massachusetts. Sources include: 2010 Census Report; Community Profiles, Department of Housing and Community Development; Historic Atlas of Massachusetts, University of Massachusetts Press 1991.Data source: https://www.sec.state.ma.us/divisions/cis/historical/incorporation-settlement.htmFeature service also available.

The 2022 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 cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

This map service from MassGIS displays the 26 Massachusetts Gateway Cities, municipalities with:population greater than 35,000 and less than 250,000;median household income below the state average;and rate of educational attainment of a bachelor’s degree or above that is below the state average.Read more about Gateway CitiesFeature service also available.

U.S. Census Bureau QuickFacts statistics for Townsend town, Middlesex 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.

The 2015 cartographic boundary shapefiles 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.

Background and Data Limitations The Massachusetts 1830 map series represents a unique data source that depicts land cover and cultural features during the historical period of widespread land clearing for agricultural. To our knowledge, Massachusetts is the only state in the US where detailed land cover information was comprehensively mapped at such an early date. As a result, these maps provide unusual insight into land cover and cultural patterns in 19th century New England. However, as with any historical data, the limitations and appropriate uses of these data must be recognized: (1) These maps were originally developed by many different surveyors across the state, with varying levels of effort and accuracy. (2) It is apparent that original mapping did not follow consistent surveying or drafting protocols; for instance, no consistent minimum mapping unit was identified or used by different surveyors; as a result, whereas some maps depict only large forest blocks, others also depict small wooded areas, suggesting that numerous smaller woodlands may have gone unmapped in many towns. Surveyors also were apparently not consistent in what they mapped as ‘woodlands’: comparison with independently collected tax valuation data from the same time period indicates substantial lack of consistency among towns in the relative amounts of ‘woodlands’, ‘unimproved’ lands, and ‘unimproveable’ lands that were mapped as ‘woodlands’ on the 1830 maps. In some instances, the lack of consistent mapping protocols resulted in substantially different patterns of forest cover being depicted on maps from adjoining towns that may in fact have had relatively similar forest patterns or in woodlands that ‘end’ at a town boundary. (3) The degree to which these maps represent approximations of ‘primary’ woodlands (i.e., areas that were never cleared for agriculture during the historical period, but were generally logged for wood products) varies considerably from town to town, depending on whether agricultural land clearing peaked prior to, during, or substantially after 1830. (4) Despite our efforts to accurately geo-reference and digitize these maps, a variety of additional sources of error were introduced in converting the mapped information to electronic data files (see detailed methods below). Thus, we urge considerable caution in interpreting these maps. Despite these limitations, the 1830 maps present an incredible wealth of information about land cover patterns and cultural features during the early 19th century, a period that continues to exert strong influence on the natural and cultural landscapes of the region.

    Acknowledgements
    Financial support for this project was provided by the BioMap Project of the Massachusetts Natural Heritage and Endangered Species Program, the National Science Foundation, and the Andrew Mellon Foundation. This project is a contribution of the Harvard Forest Long Term Ecological Research Program.

To access parcel information:Enter an address or zoom in by using the +/- tools or your mouse scroll wheel. Parcels will draw when zoomed in.Click on a parcel to display a popup with information about that parcel.Click the "Basemap" button to display background aerial imagery.From the "Layers" button you can turn map features on and off.Complete Help (PDF)Parcel Legend:Full Map LegendAbout this ViewerThis viewer displays land property boundaries from assessor parcel maps across Massachusetts. Each parcel is linked to selected descriptive information from assessor databases. Data for all 351 cities and towns are the standardized "Level 3" tax parcels served by MassGIS. More details ...Read about and download parcel dataUpdatesV 1.1: Added 'Layers' tab. (2018)V 1.2: Reformatted popup to use HTML table for columns and made address larger. (Jan 2019)V 1.3: Added 'Download Parcel Data by City/Town' option to list of layers. This box is checked off by default but when activated a user can identify anywhere and download data for that entire city/town, except Boston. (March 14, 2019)V 1.4: Data for Boston is included in the "Level 3" standardized parcels layer. (August 10, 2020)V 1.4 MassGIS, EOTSS 2021

Effective January 2023.More information: Visit the Geographic Information System (GIS) webpage for access to additional City maps.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.

Worcester Atlas is a new map viewer developed by the City of Worcester's Department of Innovation & Technology that replaces the City Property Viewer application. It provides public access to property data from the City's assessing and Geographic Information System (GIS) databases. Besides property data, you can also view many other City and State map layers too. Scroll down to learn more about Worcester Atlas and how to use it.

U.S. Census Bureau QuickFacts statistics for Weymouth Town city, 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.

The CT Municipalities layer consists of individual polygons representing each of the 169 municipalities that make up the state of Connecticut. This feature class is based on the Towns layer originally created by CTDEEP from USGS maps. The towns from the CTDEEP data were dissolved to create 169 records (one for each town). Fields were added and deleted to create a generic schema.

The CT Municipalities feature class was created in (municipality) alphabetical order. Fields were added to identify the municipality number and the CTDOT Municipality number, which differ from each other in some cases. In 1947 the town of Saybrook officially changed its name to Deep River. Other State agencies and municipalities changed their numbering systems to reflect this name change, however, most of what is now CTDOT kept their existing numbering system. This is why the CTDOT town number for Deep River is 122, the number formerly assigned to Saybrook.

The square miles associated with each town are for their interior land mass area. Coastal communities have boundaries that extend into Long Island Sound. These town boundary extensions into Long Island Sound are not included in the square miles field.

CTDOT has created and will maintain a cartographic rendering of the geometric shape of Municipal boundaries. Official Town and City designations as incorporated areas consisting of an authorized governing body are managed by CT's Office of Policy and Management (OPM).

CTDOT has undertaken a good faith effort to represent the boundaries cartographically in a fair and equitable fashion, from the best available data compiled from existing state, regional, and local resources including - existing historical cartographic renderings of the boundary locations, supplemental survey information, and map submissions. Corrections can be submitted to the CTDOT for incorporation and correction where applicable.

Attribution was assigned to designations managed by a variety of entities that strictly follow Municipal boundaries and additional designations will be added as requested by State, regional, and local partners.

U.S. Census Bureau QuickFacts statistics for Randolph Town city, 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.

The symbology of the data in this hosted tile layer is optimized for display atop aerial (ortho) imagery. Tiles are available for levels 7 through 20.Map Features for imagery include:

Political Boundaries: Massachusetts cities and towns, counties and state border, MassGIS).Transportation: Massachusetts Department of Transportation (MassDOT) Roads (MassDOT, MassGIS); MBTA subway and Commuter Rail lines and stations (Central Transportation Planning Staff, MassGIS); Airports, Ferry Routes and Seaports (MassDOT); Airport Runways and Airfields (Massachusetts Emergency Management Agency (MEMA)).Infrastructure and Facilities: Lighthouses and Lights (Massachusetts Coastal Zone Management); Licensed Child Care Programs (Department of Early Education and Care); Schools (Pre-K-High School) (Massachusetts Department of Education, MassGIS); Colleges and Universities (MassGIS); Acute Care Hospitals and Non-acute Care Hospitals (Massachusetts Department of Public Health Office of Emergency Medical Services, CHIA); Libraries, Police Stations, Fire Stations, Town Halls, Places of Worship, Courthouses, Prisons, DCR Pools.This service is used in the MassGIS Image Basemap.

Census Current (2022) Legal and Statistical Entities Web Map Service; January 1, 2022 vintage.

County Subdivisions are the primary divisions of counties and equivalent entities. They include census county divisions, census subareas, minor civil divisions, and unorganized territories, and can be classified as either legal or statistical. Legal entities are termed minor civil divisions and statistical entities can be either census county divisions, census subareas, or unorganized territories.

Minor Civil Divisions (MCDs) are the primary governmental or administrative divisions of a county in many states (parishes in Louisiana) and of the county equivalents in Puerto Rico and the Island Areas. MCDs in the United States, Puerto Rico, and the Island Areas represent many different kinds of legal entities with a wide variety of governmental and/or administrative functions. MCDs include areas variously designated as barrios, barrios-pueblo, boroughs, charter townships, commissioner districts, election districts, election precincts, gores, grants, locations, magisterial districts, parish governing authority districts, plantations, purchases, reservations, supervisor's districts, towns, and townships. The Census Bureau recognizes MCDs in 29 states, Puerto Rico, and the Island Areas. The District of Columbia has no primary divisions, and is considered equivalent to an MCD for statistical purposes.

In some states, all or some incorporated places are not part of any MCD; these places are termed independent places. In nine states-Maine, Massachusetts, New Hampshire, New Jersey, North Dakota, Pennsylvania, Rhode Island, South Dakota, and Wisconsin-all incorporated places are independent places. In other states, incorporated places are part of, or dependent within, the MCDs in which they are located, or the pattern is mixed-some incorporated places are independent of MCDs and others are included within one or more MCDs.

In New York and Maine, American Indian reservations (AIRs) generally exist outside the jurisdiction of any town (MCD) and thus also serve as the equivalent of MCDs for purposes of data presentation.

In states with legal MCDs, the Census Bureau assigns a default FIPS county subdivision code of 00000 and ANSI code of eight zeroes in some coastal, territorial sea, and Great Lakes water where county subdivisions do not extend into the Great Lakes or out to the three-mile limit.

Census County Divisions (CCDs) are areas delineated by the Census Bureau in cooperation with state, tribal, and local officials for statistical purposes. CCDs have no legal function and are not governmental units. CCD boundaries usually follow visible features and usually coincide with census tract boundaries. The name of each CCD is based on a place, county, or well-known local name that identifies its location.

Census Subareas are statistical subdivisions of boroughs, city and boroughs, municipalities, and census areas, the statistical equivalent entities for counties in Alaska. The state of Alaska and the Census Bureau cooperatively delineate the census subareas to serve as the statistical equivalents of MCDs.

Unorganized Territories (UTs) are defined by the Census Bureau in nine MCD states where portions of counties or equivalent entities are not included in any legally established MCD or incorporated place. The Census Bureau recognizes such separate pieces of territory as one or more separate county subdivisions for census purposes. It assigns each unorganized territory a descriptive name, followed by the designation "UT".

Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks.

This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

Spatial extent
This subdataset covers the North East CONUS, i.e.

• CT
• DC
• DE
• MA
• MD
• ME
• NH
• NJ
• NY
• PA
• RI
• VA

For the remaining CONUS, see the related identifiers.

Temporal extent
The map is representative for ca. 2018.

Data format
The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

• t at 10m x 10m
• kt at 100m x 100m
• Mt at 1km x 1km
• Gt at 10km x 10km

For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv.

Material layers
Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers):

A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337.

Further information
For further information, please see the publication.
A web-visualization of this dataset is available here.
Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Publication
D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. Nature Communications 14, 8014. https://doi.org/10.1038/s41467-023-43755-5

Funding
This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404.

Acknowledgments
We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

Humanity’s role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the ‘anthropocene’, as humans are ‘overwhelming the great forces of nature’. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed ‘manufactured capital’, ‘technomass’, ‘human-made mass’, ‘in-use stocks’ or ‘socioeconomic material stocks’, they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with ‘real’ (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called ‘built structures’) represent the overwhelming majority of all socioeconomic material stocks.

This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

Spatial extent
This subdataset covers the Great Plains CONUS, i.e.

• KS
• ND
• NE
• OK
• SD

For the remaining CONUS, see the related identifiers.

Temporal extent
The map is representative for ca. 2018.

Data format
The data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

• t at 10m x 10m
• kt at 100m x 100m
• Mt at 1km x 1km
• Gt at 10km x 10km

For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv.

Material layers
Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers):

A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337.

Further information
For further information, please see the publication.
A web-visualization of this dataset is available here.
Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Publication
D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gomez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, H. Haberl. Weighing the US Economy: Map of Built Structures Unveils Patterns in Human-Dominated Landscapes. In prep

Funding
This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404.

Acknowledgments
We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.