This tile service is derived from a digital raster graphic of the historical 15-minute USGS topographic quadrangle maps of coastal towns in Massachusetts. These quadrangles were mosaicked together to create a single data layer of the coast of Massachusetts and a large portion of the southeastern area of the state.The Massachusetts Office of Coastal Zone Management (CZM) obtained the map images from the Harvard Map Collection. The maps were produced in the late 1890s and early 20th century at a scale of 1:62,500 or 1:63,360 and are commonly known as 15-minute quadrangle maps because each map covers a four-sided area of 15 minutes of latitude and 15 minutes of longitude.

The surficial geologic map of the Eastern and Central United States depicts the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the “soil” in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The map is based on 31 published maps in the U.S. Geological Survey's Quaternary Geologic Atlas of the United States map series (U.S. Geological Survey Miscellaneous Investigations Series I-1420). It was compiled at 1:1,000,000 scale, to be viewed as a digital map at 1:2,000,000 nominal scale and to be printed as a conventional paper map at 1:2,500,000 scale. This map is not a map of soils as recognized and classified in agriculture. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which agricultural, agronomic, or pedologic soils are formed. Where surficial deposits or materials are thick, agricultural soils are developed only in the upper part of the engineering soils. Where they are very thin, agricultural soils are developed through the entire thickness of a surficial deposit or material. The surficial geologic map provides a broad overview of the areal distribution of surficial deposits and materials. It identifies and depicts more than 150 types of deposits and materials. In general, the map units are divided into two major categories, surface deposits and residual materials. Surface deposits are materials that accumulated or were emplaced after component particles were transported by ice, water, wind, or gravity. The glacial sediments that cover the surface in much of the northern United States east of the Rocky Mountains are in this category, as are the gravel, sand, silt, and clay that were deposited in past and present streams, lakes, and oceans. In contrast, residual materials formed in place, without significant transport of component particles by ice, water, wind, or gravity. They are products of modification or alteration of pre-existing surficial deposits, surficial materials, or bedrock. For example, intense weathering of solid rock, or even stream deposits, by chemical processes may produce a residual surficial material that is greatly transformed from its original physical and chemical state. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident The map and its digital database provide information about four major aspects of the surficial materials, through description of more than 150 types of materials and depiction of their areal distribution. The map unit descriptions provide information about (1) genesis (processes of origin) or environments of deposition (for example, deposits related to glaciation (glacial deposits), flowing water (alluvial deposits), lakes (lacustrine deposits), wind (eolian deposits), or gravity (mass-movement deposits)), (2) age (for example, how long ago the deposits accumulated or were emplaced or how long specific processes have been acting on the materials), (3) properties (the chemical, physical, and mechanical or engineering characteristics of the materials), and (4) thickness or depth to underlying deposits or materials or to bedrock. This approach provides information appropriate for a broad user base. The map is useful to national, state, and other governmental agencies, to engineering and construction companies, to environmental organizations and consultants, to academic scientists and institutions, and to the layman who merely wishes to learn more about the materials that conceal the bedrock. The map can facilitate regional and national overviews of (1) geologic hazards, including areas of swelling clay and areas of landslide deposits and landslide-prone materials, (2) natural resources, including aggregate for concrete and road building, peat, clay, and shallow sources for groundwater, and (3) areas of special environmental concern, i... Visit https://dataone.org/datasets/d863e647-d00d-4994-89bc-be4be9d4adf0 for complete metadata about this dataset.

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 extentThis dataset covers the whole CONUS. Due to upload constraints, detailed data were split into 7 regions and were uploaded into sub-repositories - see related identifiers. (This repository holds aggregated values for the whole CONUS)

Great Plains Mid West North East Rocky Mountains South South West West Coast Temporal extentThe map is representative for ca. 2018. Data formatThe 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 layersNote 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 informationFor 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. PublicationD. 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 FundingThis 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. AcknowledgmentsWe 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, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.

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 dataset covers the whole CONUS. Due to upload constraints, detailed data were split into 7 regions and were uploaded into sub-repositories - see related identifiers. (This repository holds aggregated values for the whole CONUS) Great Plains Mid West North East Rocky Mountains South South West West Coast 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, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

The USGS Woods Hole Science Center conducted a nearshore geophysical survey offshore of the southern coast of Martha's Vineyard, in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO) in August 2007. This mapping program was part of a larger research effort supporting the Office of Naval Research (ONR) Ripples Directed-Research Initiative (DRI) studies at MVCO by providing data collection and modeling. The geophysical data will be used to provide initial conditions for wave and circulation models for the study area. Ultimately, geophysical mapping, oceanographic measurements and modeling will help to improve our understanding of coastal sediment-transport processes.

The geophysical mapping utilized a suite of high-resolution instrumentation to map the surficial sediment distribution, depth and sub-surface geology: dual-frequency 100/500 KHz sidescan-sonar system, 234-KHz interferometric sonar, and 500 Hz -12 KHz chirp sub-bottom profiler. The survey was conducted aboard the M/V Megan Miller August 9-13, 2007. The study area covers 35 square kilometers from about 0.2 km to 5-km offshore of the south shore of Martha's Vineyard, and ranges in depth from ~ 5 to 20 meters.

The USGS Woods Hole Science Center conducted a nearshore geophysical survey offshore of the southern coast of Martha's Vineyard, in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO) in August 2007. This mapping program was part of a larger research effort supporting the Office of Naval Research (ONR) Ripples Directed-Research Initiative (DRI) studies at MVCO by providing data collection and modeling. The geophysical data will be used to provide initial conditions for wave and circulation models for the study area. Ultimately, geophysical mapping, oceanographic measurements and modeling will help to improve our understanding of coastal sediment-transport processes.

The geophysical mapping utilized a suite of high-resolution instrumentation to map the surficial sediment distribution, depth and sub-surface geology: dual-frequency 100/500 KHz sidescan-sonar system, 234-KHz interferometric sonar, and 500 Hz -12 KHz chirp sub-bottom profiler. The survey was conducted aboard the M/V Megan Miller August 9-13, 2007. The study area covers 35 square kilometers from about 0.2 km to 5-km offshore of the south shore of Martha's Vineyard, and ranges in depth from ~ 5 to 20 meters.

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.