Supervised learning for automated feature selection in road network generalization
Izabela Karsznia
Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
Albert Adolf
Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
Stefan Leyk
Department of Geography, University of Colorado Boulder, USA
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Preprint under review for ESSD
Short summary
Short summary
To better understand how wildfires threaten and affect human settlements and to model the effects of nuclear war and other hazards, detailed data on burnable materials of the built environment are crucial, but have not been available. COMBUST aims to fill this gap and provides estimates of the combustible mass of building materials, building contents, gas stations, refineries, and personal vehicles for the conterminous United States, at high spatial resolution and over time from 1975 to 2020.
Albert Adolf and Izabela Karsznia
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Iga Ajdacka and Izabela Karsznia
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Aleksander Berg and Stefan Leyk
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Abstr. Int. Cartogr. Assoc., 10, 92, https://doi.org/10.5194/ica-abs-10-92-2025, https://doi.org/10.5194/ica-abs-10-92-2025, 2025
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Short summary
Short summary
Historical, fine-grained geospatial datasets on built-up areas are rarely available, constraining studies of urbanization, settlement evolution, or the dynamics of human–environment interactions to recent decades. In order to provide such historical data, we used publicly available cadastral building data for Spain and created a series of gridded surfaces, measuring age, physical, and land-use-related features of the built environment in Spain and the evolution of settlements from 1900 to 2020.
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