{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T14:53:58Z","timestamp":1767192838404,"version":"build-2065373602"},"reference-count":77,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T00:00:00Z","timestamp":1704412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42271089","42101311","42371084"],"award-info":[{"award-number":["42271089","42101311","42371084"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the context of urbanization, frequent flood event have become the most common natural disasters, posing a significant challenge to human society. Considering the effects of urbanization on flood risk is critical for flood risk reduction and reasonable land planning strategies at the city scale. This study proposes an integrated approach based on remote sensing data using CA, Markov, and simplified hydrodynamic (FloodMap) models to accurately and effectively assess flood risk under urbanization. Taking Chongqing City as a case study, this paper analyzes the temporal and spatial variations in land use\/land cover (LULC) in 2010, 2015, and 2018 and predicts the LULC for 2030, based on historic trends. Flood risk is assessed by combining the hazard, exposure, and modified vulnerability. The results suggest that the area of built-up land will increase significantly from 19.56% in 2018 to 25.21% in 2030. From 2010 to 2030, the area of medium and high inundation depths will increase by 10 and 16 times, respectively. Flood damage varies remarkably according to the LULC and return period. The expected annual damage (EAD) has been estimated to increase from USD 68 million in 2010 to USD 200 million in 2030. Flood risk is proportional to population and is significantly inversely proportional to socioeconomic level. The approach used here can provide a comprehensive understanding of flood risk and is significant for land-use policymaking and the management of flood control facilities.<\/jats:p>","DOI":"10.3390\/rs16020219","type":"journal-article","created":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T07:38:31Z","timestamp":1704440311000},"page":"219","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Flood Risk Assessment of Areas under Urbanization in Chongqing, China, by Integrating Multi-Models"],"prefix":"10.3390","volume":"16","author":[{"given":"Yuqing","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3161-1763","authenticated-orcid":false,"given":"Jiangbo","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jie","family":"Yin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China"},{"name":"School of Geographic Sciences, East China Normal University, Shanghai 200241, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3086-2686","authenticated-orcid":false,"given":"Lulu","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Chuanwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Shaohong","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,5]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2021). 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