The Crop Map of England (CROME) North is a polygon vector dataset mainly containing the crop types of England. The dataset contains approximately 32 million hexagonal cells classifying England into over 20 main crop types, grassland, and non-agricultural land covers, such as Woodland, Water Bodies, Fallow Land and other non-agricultural land covers. The classification was created automatically using supervised classification (Random Forest Classification) from the combination of Sentinel-1 and Sentinel-2 images during the period late January 2016 – August 2016. The dataset was created to aid the classification of crop types from optical imagery, which can be affected by cloud cover. The results were checked against survey data collected by field inspectors and visually validated. refer to the CROME specification document Attribution statement: © Rural Payments Agency

A PDF map showing the lower layer super output areas in the North East Region of England as at December 2011. (File Size - 15 MB)

The Crop Map of England (CROME) is a polygon vector dataset mainly containing the crop types of England. The dataset contains approximately 32 million hexagonal cells classifying England into over 50 main crop types, grassland, and non-agricultural land covers, such as Trees, Water Bodies, Fallow Land and other non-agricultural land covers. The classification was created automatically using supervised classification (Random Forest Classification) from the combination of Sentinel-1 and Sentinel-2 images during the period late January 2017 – August 2017. The dataset was created to aid the classification of crop types from optical imagery, which can be affected by cloud cover. The results were checked against survey data collected by field inspectors and visually validated. Refer to the CROME specification document. Attribution statement:

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2017 (LCM2017) representing Northern Ireland. It describes Northern Ireland's land cover in 2017 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2017 20m classified pixels dataset. All further LCM2017 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2017 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2017. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2017. LCM2017 was simultaneously released with LCM2018 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Northern Ireland. It describes Northern Ireland's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2019 20m classified pixels dataset. All further LCM2019 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value and a range of per-parcel pixel statistics to help assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

A PDF map showing the middle layer super output areas in the North East Region of England as at December 2011. (File Size - 14 MB)

Topographic maps of North and North-East Greenland 1:250 000 Data collected from aerial photographs at nomimal scale 1:150 000 by the Danish Geodetic Institute in the period 1978 - 1987; rectified using ground control and aerotriangulation from the National Survey and Cadastre (KMS) (permission A.200/87). The map sheet extent and the numbers of the map sheets are based on the two map series at scale 1:250 000 and 1:100 000 of KMS. Geodetic reference: WGS84, Projection: Universal Transverse Mercator, zone 24 N.

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. 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.

The data shows superficial polygons, bedrock polygons and fault linear geological information, sourced from published Geological Survey of Northern Ireland 1:250 000 scale maps - superficial (Quaternary 1991) and bedrock (Solid 1997). Full Northern Ireland coverage is available (Bedrock extends west into RI). The data is available in vector format. BGS licensing terms and conditions apply to external use of the data. New version available: 1:250K Geological Maps of Northern Ireland version 2

The Digital Geomorphic-GIS Map of Cape Lookout National Seashore, North Carolina (1:10,000 scale 2008 mapping) is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (calo_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (calo_geomorphology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (calo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (calo_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (calo_geomorphology_metadata_faq.pdf). Please read the calo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: East Carolina University. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (calo_geomorphology_metadata.txt or calo_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:10,000 and United States National Map Accuracy Standards features are within (horizontally) 8.5 meters or 27.8 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This is the land parcel (polygon) dataset for the UKCEH Land Cover Map of 2020 (LCM2020) representing Northern Ireland. It describes Northern Ireland's land cover in 2020 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value and a range of per-parcel pixel statistics to help assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation accompanying this dataset. LCM2020 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2020. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2020. These are one of a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps in 2000, 2007, 2015 and annually since 2017. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/36343ace-d56a-43ea-9d48-2f434dafcb26

A PDF map showing the Rural Urban Classification (2011) of the MSOAs in the North East Region. (File Size - 365 KB)

A PDF map showing the output areas in the North West Region of England as at December 2011. (File Size - 33 MB)

A PDF map showing the Rural Urban Classification (2011) of the OAs in the North East Region. (File Size - 850 KB)

At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.

What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.

How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.

Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:

Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.

Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.

Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.

In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Northern Ireland. It describes Northern Ireland's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

A PDF map showing the output areas in the North East Region of England as at December 2011. (File Size - 15 MB)

This dataset consists of a 1km resolution raster version of the Land Cover Map 2000 for Northern Ireland. Each 1km pixel represents the dominant target class (or 'sub class') across the 1km area. The target classes broadly represent Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

The 1:250k Geological Maps of Northern Ireland comprise the Superficial Deposits Map (Drift, 1991) and the Bedrock Map (Solid Geology, 1997). These maps identify landscape areas based on their lithology. The scale of the maps is 1:250 000 and provides a simplified interpretation of the geology that may be used as a guide at a regional level, but should not be relied on for local geology. Superficial deposits are younger geological deposits formed during the most recent geological time; the Quaternary. These deposits rest on older rocks or deposits referred to as bedrock. The superficial deposits theme defines landscape areas with a geological name and their deposit-type or lithological composition. The Superficial map shows the deposits within the extent of the six Counties of Northern Ireland. The Bedrock map comprises the bedrock geology and contains dykes and geological faults. Bedrock geology describes the main mass of solid rocks forming the earth's crust. Bedrock is present everywhere, whether exposed at surface in outcrops or concealed beneath superficial deposits or water bodies. Geological names are based on the lithostratigraphic or lithodemic hierarchy of the rocks. The lithostratigraphic scheme arranges rock bodies into units based on rock-type and geological time of formation. Where rock-types do not fit into the lithostratigraphic scheme, for example intrusive, deformed rocks subjected to heat and pressure resulting in new or changed rock types; then their classification is based on their rock-type or lithological composition. This assesses visible features such as texture, structure, mineralogy. Dykes defines small, narrow areas of a specific type of bedrock geology; that is igneous rocks which have been intruded into the landscape at a later date than the surrounding bedrock. Geological faults occur where a body of bedrock has been fractured and displaced by large scale processes affecting the earth's crust (tectonic forces). The Bedrock map shows the main bedrock geological divisions in Northern Ireland and coverage extends to the west into the Republic of Ireland. The printed map includes a stratigraphic column. Digital datasets have been derived from the maps and comprise three layers. 1. Superficial polygons, 2. Bedrock polygons and 3. Linear features. Attribute tables describe the polygon features. These data are generalised and superseded by the 1:10k Geological Maps of Northern Ireland.