{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T03:24:33Z","timestamp":1785900273046,"version":"3.56.0"},"reference-count":99,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T00:00:00Z","timestamp":1631577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1563933"],"award-info":[{"award-number":["1563933"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1564164"],"award-info":[{"award-number":["1564164"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1924670"],"award-info":[{"award-number":["1924670"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P2CHD066613"],"award-info":[{"award-number":["P2CHD066613"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature\u2013human systems (e.g., the dynamics of the wildland\u2013urban interface). Herein, we propose a framework that jointly uses remote-sensing-derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color space segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach against historical building density estimates from the Historical Settlement Data Compilation for the US (HISDAC-US), and against urban area estimates from the History Database of the Global Environment (HYDE). Our results achieve Area-under-the-Curve values &gt;0.9 when comparing to HISDAC-US and are largely in agreement with model-based urban areas from the HYDE database, demonstrating that the integration of remote-sensing-derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization and long-term land cover change in countries where historical maps are available.<\/jats:p>","DOI":"10.3390\/rs13183672","type":"journal-article","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T21:47:21Z","timestamp":1631656041000},"page":"3672","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4861-5915","authenticated-orcid":false,"given":"Johannes H.","family":"Uhl","sequence":"first","affiliation":[{"name":"Earth Lab, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USA"},{"name":"Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9180-4853","authenticated-orcid":false,"given":"Stefan","family":"Leyk","sequence":"additional","affiliation":[{"name":"Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA"},{"name":"Department of Geography, University of Colorado Boulder, Boulder, CO 80309, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zekun","family":"Li","sequence":"additional","affiliation":[{"name":"Spatial Sciences Institute, University of Southern California, Los Angeles, CA 90089, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"Duan","sequence":"additional","affiliation":[{"name":"Spatial Sciences Institute, University of Southern California, Los Angeles, CA 90089, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Basel","family":"Shbita","sequence":"additional","affiliation":[{"name":"Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao-Yi","family":"Chiang","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, University of Minnesota, Minneapolis, MN 55455, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6371-4807","authenticated-orcid":false,"given":"Craig A.","family":"Knoblock","sequence":"additional","affiliation":[{"name":"Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,14]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division (2018). 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