{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T18:13:01Z","timestamp":1772647981618,"version":"3.50.1"},"reference-count":66,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006360","name":"Bundesministerium f\u00fcr Wirtschaft und Energie","doi-asserted-by":"publisher","award":["O20E-SY 48192 ANSWER-Kommunal"],"award-info":[{"award-number":["O20E-SY 48192 ANSWER-Kommunal"]}],"id":[{"id":"10.13039\/501100006360","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Cities are responsible for a large share of the global energy consumption. A third of the total greenhouse gas emissions are related to the buildings sector, making it an important target for reducing urban energy consumption. Detailed data on the building stock, including the thermal characteristics of individual buildings, such as the construction type, construction period, and building geometries, can strongly support decision-making for local authorities to help them spatially localize buildings with high potential for thermal renovations. In this paper, we present a workflow for deep learning-based building stock modeling using aerial images at a city scale for heat demand modeling. The extracted buildings are used for bottom-up modeling of the residential building heat demand based on construction type and construction period. The results for DL-building extraction exhibit F1-accuracies of 87%, and construction types yield an overall accuracy of 96%. The modeled heat demands display a high level of agreement of R2 0.82 compared with reference data. Finally, we analyze various refurbishment scenarios for construction periods and construction types, e.g., revealing that the targeted thermal renovation of multi-family houses constructed between the 1950s and 1970s accounts for about 47% of the total heat demand in a realistic refurbishment scenario.<\/jats:p>","DOI":"10.3390\/ijgi10010023","type":"journal-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T14:28:53Z","timestamp":1610461733000},"page":"23","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Deep Learning-Based Generation of Building Stock Data from Remote Sensing for Urban Heat Demand Modeling"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5967-1894","authenticated-orcid":false,"given":"Michael","family":"Wurm","sequence":"first","affiliation":[{"name":"German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, 82234 Wessling, Germany"}]},{"given":"Ariane","family":"Droin","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, 82234 Wessling, Germany"},{"name":"Institute for Geography and Regional Planning, University of Graz, Heinrichstr. 36, 8010 Graz, Austria"}]},{"given":"Thomas","family":"Stark","sequence":"additional","affiliation":[{"name":"Signal Processing in Earth Observation, Technical University of Munich (TUM), 80333 Munich, Germany"}]},{"given":"Christian","family":"Gei\u00df","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, 82234 Wessling, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6040-2405","authenticated-orcid":false,"given":"Wolfgang","family":"Sulzer","sequence":"additional","affiliation":[{"name":"Institute for Geography and Regional Planning, University of Graz, Heinrichstr. 36, 8010 Graz, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4360-9126","authenticated-orcid":false,"given":"Hannes","family":"Taubenb\u00f6ck","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, 82234 Wessling, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,12]]},"reference":[{"key":"ref_1","unstructured":"European Environment Agency (2015). 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