{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:51:20Z","timestamp":1767340280179,"version":"build-2065373602"},"reference-count":94,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T00:00:00Z","timestamp":1651104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"LabEx DRIHM, French Programme \u201cInvestissements d\u2019Avenir\u201d","award":["ANR-11-LABX-0010"],"award-info":[{"award-number":["ANR-11-LABX-0010"]}]},{"name":"Land Change Science Program of the U.S. Geological Survey","award":["ANR-11-LABX-0010"],"award-info":[{"award-number":["ANR-11-LABX-0010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Tucson metropolitan area, located in the Sonoran Desert of southeastern Arizona (USA), is affected by both massive population growth and rapid climate change, resulting in important land use and land cover (LULC) changes. As its fragile arid ecosystem and scarce resources are increasingly under pressure, there is a crucial need to monitor such landscape transformations. For such ends, we propose a method to compute yearly 30 m resolution LULC maps of the region from 1986 to 2020, using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier. The entire process was hosted in the Google Earth Engine with tremendous computing capacities that allowed us to process a large amount of data and to achieve high overall classification accuracy for each year, ranging from 86.7 to 96.3%. Conservative post-processing techniques were also used to mitigate the persistent confusions between the numerous isolated houses in the region and their desert surroundings and to smooth year-specific LULC changes in order to identify general trends. We then show that policies to lessen urban sprawl in the area had little effects and we provide an automated tool to continue monitoring such dynamics in the future.<\/jats:p>","DOI":"10.3390\/rs14092127","type":"journal-article","created":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T22:20:06Z","timestamp":1651184406000},"page":"2127","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Monitoring Annual Land Use\/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986\u20132020)"],"prefix":"10.3390","volume":"14","author":[{"given":"Fabrice","family":"Dubertret","sequence":"first","affiliation":[{"name":"International Research Laboratory on Interdisciplinary Global Environmental Studies (IRL iGLOBES), National Scientific Research Center (CNRS), University of Arizona, 845 N. Park Avenue, Marshall Building 5th Floor, Tucson, AZ 85719, USA"}]},{"given":"Fran\u00e7ois-Michel","family":"Le Tourneau","sequence":"additional","affiliation":[{"name":"National Scientific Research Center (CNRS)\u2014P\u00f4le de Recherche pour l\u2019Organisation et la Diffusion de l\u2019Information G\u00e9ographique (PRODIG), Campus Condorcet, B\u00e2timent Recherche Sud, 5 Cours des Humanit\u00e9s, 93300 Aubervilliers, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0720-1422","authenticated-orcid":false,"given":"Miguel L.","family":"Villarreal","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Western Geographic Science Center, Moffett Field, CA 94035, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3696-8406","authenticated-orcid":false,"given":"Laura M.","family":"Norman","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Western Geographic Science Center, Tucson, AZ 85719, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,28]]},"reference":[{"key":"ref_1","unstructured":"Sheridan, T.E. 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