• Energy Research

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 South West CONUS, i.e. AZ NM NV TX 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.

Abstract Sustainable resource use calls for substantial changes to existing infrastructures, which lock societies into current resource use patterns. Urban mobility is a case in point: existing material stocks of infrastructure and vehicles require large amounts of materials and energy for maintenance and operation in order to provide mobility services, thereby causing considerable emissions. Understanding the stock-flow-service nexus of urban mobility is crucial for achieving progress towards absolute reductions of resource use and emissions. In this article, we investigate personal mobility in an urban context - Vienna. We use stock-driven material and energy flow analysis to quantify mobility stocks and flows for four different modes of mobility: pedestrian, bicycle, public transport and motorized individual traffic (MIT). We quantify material flows for maintenance, expansion, as well as primary energy use and emissions linked to personal mobility within city territory and compare a number of stock-flow-service indicators. Public transport was found to deliver most mobility services (38%), when services were measured as trips. Pedestrian mobility showed the lowest stock intensity of services while using less energy and generating lower emissions per service than any other mobility mode. Trips crossing the city border showed high shares of motorized individual traffic (62–63%). Traffic surfaces dominated material requirements of mobility and are mainly (78%) used by MIT. We conclude that considering stock-flow-service relations can support prioritizing future urban mobility planning, highlight the importance of infrastructure-related measures in doing so and the need for better monitoring especially of mobility service indicators.

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 Mid West CONUS, i.e. IA IL IN MI MN MO OH WI 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.

AbstractBuilt structures increasingly dominate the Earth’s landscapes; their surging mass is currently overtaking global biomass. We here assess built structures in the conterminous US by quantifying the mass of 14 stock-building materials in eight building types and nine types of mobility infrastructures. Our high-resolution maps reveal that built structures have become 2.6 times heavier than all plant biomass across the country and that most inhabited areas are mass-dominated by buildings or infrastructure. We analyze determinants of the material intensity and show that densely built settlements have substantially lower per-capita material stocks, while highest intensities are found in sparsely populated regions due to ubiquitous infrastructures. Out-migration aggravates already high intensities in rural areas as people leave while built structures remain – highlighting that quantifying the distribution of built-up mass at high resolution is an essential contribution to understanding the biophysical basis of societies, and to inform strategies to design more resource-efficient settlements and a sustainable circular economy.

Les infrastructures de mobilité routière et ferroviaire sont à la base des services de mobilité et sous-tendent plusieurs objectifs de développement durable, mais induisent également une utilisation des matériaux et des émissions de gaz à effet de serre. À ce jour, aucune étude cohérente stock-flux n'a évalué les stocks mondiaux accumulés d'infrastructures de mobilité, les flux et émissions de matériaux associés et leurs schémas spatiaux. Nous présentons les résultats mondiaux sur les stocks de matériaux pour toutes les routes, les infrastructures ferroviaires, y compris les tunnels et les ponts, et modélisons les flux de matériaux associés et leurs émissions intrinsèques pour l'année 2021. Le modèle cohérent stock-flux combine des données Open Street Maps provenant de la foule avec des conceptions d'infrastructure archétypales, des compositions matérielles, des hypothèses sur les durées de vie et les taux de croissance du réseau, y compris les plages d'incertitude. Nous dérivons des estimations de stocks spatialement explicites au niveau national pour 180 pays et les cartographions à une résolution de 5 minutes d'arc, et dérivons des flux de matières et des émissions incorporées au niveau des pays. Nous constatons que 314 [218-403] Gt de matériaux (41 [28–53] tonnes/cap) se sont accumulés dans les infrastructures de mobilité mondiales, la majorité dans les routes sous forme d'agrégats et d'asphalte. Les stocks sont inégalement répartis entre les pays, de 23 [16–30] tonnes/cap en moyenne dans les pays à faible revenu, à 130 [89–164] tonnes/cap dans les pays à revenu élevé. L'inégalité spatiale des stocks par habitant par zone diffère selon les ordres de grandeur, de 101 à 104 entre les zones rurales, suburbaines et urbaines denses. Nous constatons que 8 [4–16] Gt/an de flux de matières sont dus à l'expansion et à la maintenance, soit 6 [3–10] % de l'extraction mondiale des ressources. Celles-ci se traduisent par 0,36 [0,19-0,69] Gt éq CO2/an, soit 1 [0,5-1,9] % des émissions mondiales de GES en 2021. Environ les deux tiers de ces flux résultent de l'entretien et du remplacement des stocks, ce qui indique un verrouillage important de l'utilisation des ressources en raison des stocks d'infrastructures déjà existants. Ces résultats confirment le rôle crucial de l'amélioration de l'aménagement du territoire, de la limitation de l'expansion des stocks et de la (sous-)urbanisation, pour parvenir à une utilisation plus durable des ressources et atténuer le changement climatique. Las carreteras y las infraestructuras de movilidad ferroviarias son la base de los servicios de movilidad y sustentan varios Objetivos de Desarrollo Sostenible, pero también inducen el uso de materiales y las emisiones de gases de efecto invernadero. Hasta la fecha, ningún estudio consistente de stock-flujo ha evaluado las existencias acumuladas a nivel mundial de infraestructuras de movilidad, los flujos y emisiones de materiales asociados y sus patrones espaciales. Presentamos los resultados globales sobre las existencias de materiales para todas las carreteras, infraestructuras ferroviarias, incluidos túneles y puentes, y los flujos de materiales asociados al modelo y sus emisiones incorporadas para el año 2021. El modelo consistente de stock-flujo combina datos de Open Street Maps de fuentes múltiples con diseños de infraestructura arquetípicos, composiciones de materiales, suposiciones sobre la vida útil y las tasas de crecimiento de la red, incluidos los rangos de incertidumbre. Derivamos estimaciones de existencias a nivel nacional espacialmente explícitas para 180 países y las mapeamos a una resolución de 5 minutos de arco, y derivamos flujos de materiales y emisiones incorporadas a nivel de país. Encontramos que 314 [218-403] Gt de materiales (41 [28–53] toneladas/cap) se han acumulado en la infraestructura de movilidad global, la mayoría en carreteras como áridos y asfalto. Las existencias se distribuyen de manera desigual entre los países, desde promedios de 23 [16–30] toneladas/límite en los países de bajos ingresos, hasta 130 [89–164] toneladas/límite en los países de altos ingresos. La desigualdad espacial de las poblaciones per cápita por área difiere en órdenes de magnitud, de 101 a 104 entre las áreas rurales, suburbanas y urbanas densas. Encontramos que 8 [4–16] Gt/año de flujos de materiales se deben a la expansión y el mantenimiento, que ascienden al 6 [3–10] % de la extracción global de recursos. Estos se traducen en 0.36 [0.19–0.69] Gt CO2eq/año, o 1 [0.5–1.9] % de las emisiones globales de GEI en 2021. Aproximadamente dos tercios de estos flujos son el resultado del mantenimiento y la sustitución de existencias, lo que indica un importante bloqueo del uso de recursos debido a las existencias de infraestructura ya existentes. Estos hallazgos respaldan el papel crucial de mejorar la planificación espacial, limitar la expansión de las poblaciones y la (sub)urbanización, para lograr un uso más sostenible de los recursos y mitigar el cambio climático. Roads and rail-based mobility infrastructures are the basis for mobility services and underpin several Sustainable Development Goals, but also induce material use and greenhouse gas emissions. To date, no stock-flow consistent study has assessed globally accumulated stocks of mobility infrastructures, associated material flows and emissions, and their spatial patterns. We present global findings on material stocks for all roads, rail-based infrastructures, incl. tunnels and bridges, and model associated material flows and their embodied emissions for the year 2021. The stock-flow consistent model combines crowd-sourced Open Street Maps data with archetypical infrastructure designs, material compositions, assumptions on lifetimes and network growth rates, incl. uncertainty ranges. We derive spatially explicit, national-level stock estimates for 180 countries and map them at a resolution of 5 arcminutes, and derive material flows and embodied emissions at the country-level. We find that 314 [218–403] Gt of materials (41 [28–53] tons/cap) have accumulated in global mobility infrastructure, the majority in roads as aggregates and asphalt. Stocks are unequally distributed between countries, from averages of 23 [16–30] tons/cap in low income countries, to 130 [89–164] tons/cap in high income countries. Spatial inequality of per capita stocks per area differs by orders of magnitude, from 101-104 between rural, suburban, and dense urban areas. We find that 8 [4–16] Gt/year of material flows are due to expansion and maintenance, amounting to 6 [3–10] % of global resource extraction. These translate into 0.36 [0.19–0.69] Gt CO2eq/year, or 1 [0.5–1.9] % of global GHG emissions in 2021. Approximately two-thirds of these flows result from maintenance and replacement of stocks, indicating an important lock-in of resource use due to already existing infrastructure stocks. These findings support the crucial role of improving spatial planning, limiting stock expansion and (sub-)urbanization, to achieve more sustainable resource use and mitigate climate change. تعد الطرق والبنى التحتية للتنقل القائم على السكك الحديدية أساس خدمات التنقل وتدعم العديد من أهداف التنمية المستدامة، ولكنها تحفز أيضًا استخدام المواد وانبعاثات غازات الدفيئة. حتى الآن، لم تقم أي دراسة متسقة لتدفق المخزون بتقييم المخزونات المتراكمة عالميًا من البنى التحتية للتنقل، وتدفقات المواد والانبعاثات المرتبطة بها، وأنماطها المكانية. نقدم نتائج عالمية حول مخزونات المواد لجميع الطرق والبنية التحتية القائمة على السكك الحديدية، بما في ذلك الأنفاق والجسور، ونموذج تدفقات المواد المرتبطة بها وانبعاثاتها المجسدة لعام 2021. يجمع النموذج المتسق لتدفق المخزون بين بيانات خرائط الشوارع المفتوحة من مصادر جماعية مع تصميمات البنية التحتية النموذجية وتركيبات المواد والافتراضات على الأعمار ومعدلات نمو الشبكة، بما في ذلك نطاقات عدم اليقين. نستمد تقديرات المخزون المكانية الصريحة على المستوى الوطني لـ 180 دولة ونحددها بدقة 5 دقائق قوسية، ونستمد تدفقات المواد والانبعاثات المجسدة على المستوى القطري. نجد أن 314 [218-403] جيجا طن من المواد (41 [28–53] طن/غطاء) قد تراكمت في البنية التحتية للتنقل العالمي، ومعظمها في الطرق مثل الركام والأسفلت. يتم توزيع المخزونات بشكل غير متساوٍ بين البلدان، من متوسط 23 [16–30] طن/حد أقصى في البلدان منخفضة الدخل، إلى 130 [89–164] طن/حد أقصى في البلدان مرتفعة الدخل. يختلف التفاوت المكاني لمخزون الفرد لكل منطقة حسب الحجم، من 101 إلى 104 بين المناطق الريفية والضواحي والمناطق الحضرية الكثيفة. نجد أن 8 [4–16] جيجا طن/سنة من تدفقات المواد ترجع إلى التوسع والصيانة، والتي تصل إلى 6 [3–10] ٪ من استخراج الموارد العالمية. تترجم هذه إلى 0.36 [0.19-0.69] جيجا طن من مكافئ ثاني أكسيد الكربون/سنة، أو 1 [0.5–1.9 ]٪ من انبعاثات غازات الدفيئة العالمية في عام 2021. ما يقرب من ثلثي هذه التدفقات ناتجة عن صيانة واستبدال المخزونات، مما يشير إلى قفل مهم في استخدام الموارد بسبب مخزونات البنية التحتية الموجودة بالفعل. تدعم هذه النتائج الدور الحاسم لتحسين التخطيط المكاني، والحد من توسع المخزون والتحضر (الفرعي)، لتحقيق استخدام أكثر استدامة للموارد والتخفيف من تغير المناخ.

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 West Coast CONUS, i.e. CA OR WA 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.

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 subdataset covers the South CONUS, i.e. AL AR FL GA KY LA MS NC SC TN VA WV For the remaining CONUS, see the related identifiers. 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.