{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:41:26Z","timestamp":1760233286724,"version":"build-2065373602"},"reference-count":87,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["42101383"],"award-info":[{"award-number":["42101383"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In today\u2019s accelerating urbanization process, timely and effective monitoring of land-cover dynamics, landscape pattern analysis, and evaluation of built-up urban areas (BUAs) have important research significance and practical value for the sustainable development, planning and management, and ecological protection of cities. High-spatial-resolution remote sensing (HRRS) images have the advantages of high-accuracy Earth observations, covering a large area, and having a short playback period, and they can objectively and accurately provide fine dynamic spatial information about the land cover in urban built-up areas. However, the complexity and comprehensiveness of the urban structure have led to a single-scale analysis method, which makes it difficult to accurately and comprehensively reflect the characteristics of the BUA landscape pattern. Therefore, in this study, a joint evaluation method for an urban land-cover spatiotemporal-mapping chain and multi-scale landscape pattern using high-resolution remote sensing imagery was developed. First, a pixel\u2013object\u2013knowledge model with temporal and spatial classifications was proposed for the spatiotemporal mapping of urban land cover. Based on this, a multi-scale district\u2013BUA\u2013city block\u2013land cover type map of the city was established and a joint multi-scale evaluation index was constructed for the multi-scale dynamic analysis of the urban landscape pattern. The accuracies of the land cover in 2016 and 2021 were 91.9% and 90.4%, respectively, and the kappa coefficients were 0.90 and 0.88, respectively, indicating that the method can provide effective and reliable information for spatial mapping and landscape pattern analysis. In addition, the multi-scale analysis of the urban landscape pattern revealed that, during the period of 2016\u20132021, Beijing maintained the same high urbanization rate in the inner part of the city, while the outer part of the city kept expanding, which also reflects the validity and comprehensiveness of the analysis method developed in this study.<\/jats:p>","DOI":"10.3390\/rs15010074","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T07:30:06Z","timestamp":1672126206000},"page":"74","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-Level Dynamic Analysis of Landscape Patterns of Chinese Megacities during the Period of 2016\u20132021 Based on a Spatiotemporal Land-Cover Classification Model Using High-Resolution Satellite Imagery: A Case Study of Beijing, China"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9054-3759","authenticated-orcid":false,"given":"Zhi","family":"Li","sequence":"first","affiliation":[{"name":"China Center for Resources Satellite Data and Application, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Lu","sequence":"additional","affiliation":[{"name":"Zhejiang Taile Geography Information Technology Co., Ltd., Huzhou 313200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-8480","authenticated-orcid":false,"given":"Xiaomei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Jiangsu Centre for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"115630","DOI":"10.1016\/j.jenvman.2022.115630","article-title":"Population-environment dynamics across world\u2019s top 100 urban agglomerations: With implications for transitioning toward global urban sustainability","volume":"319","author":"Chen","year":"2022","journal-title":"J. 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