{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:32:18Z","timestamp":1761060738648,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,15]],"date-time":"2019-01-15T00:00:00Z","timestamp":1547510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Quantifying the temporal and spatial patterns of impervious surfaces (IS) is important for assessing the environmental and ecological impacts of urbanization. In order to better extract IS, and to explore the divergence in urbanization in different regions, research on the regional differentiation features and regional change difference features of IS are required. To extract China\u2019s 2013 urban impervious area, we used the 2013 night light (NTL) data and the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index and enhanced vegetation index (EVI) temporal series data, and used three urban impervious surface extraction indexes\u2014Human Settlements Index, Vegetation-Adjusted NTL Urban Index, and the EVI-adjusted NTL index (EANTLI)\u2014which are recognized as the best and most widely used indexes for extracting urban impervious areas. We used the classification results of the Landsat-8 images as the benchmark data to visually compare and verify the results of the urban impervious area extracted by the three indexes. We determined that the EANTLI index better reflects the distribution of the impervious area. Therefore, we used the EANTLI index to extract the urban impervious area from 2003 to 2013 in the study area, and researched the spatial and temporal differentiation in urban IS. The results showed that China\u2019s urban IS area was 70,179.06 km2, accounting for 0.73% of the country\u2019s land area in 2013, compared with 20,565.24 km2 in 2003, which accounted for 0.21% of the land area, representing an increase of 0.52%. On a spatial scale, like economic development, the distribution of urban impervious surfaces was different in different regions. The overall performance of the urban IS percentage was characterized by a decreasing trend from Northwest China, Southwest China, the Middle Reaches of the Yellow River, Northeast China, the Middle Reaches of the Yangtze River, Southern Coastal China, and Northern Coastal China to Eastern Coastal China. On the provincial scale, the urban IS expansion showed considerable differences in different regions. The overall performance of the Urban IS Expansion index showed that the eastern coastal areas had higher values than the western inland areas. The cities or provinces of Beijing, Tianjin, Jiangsu, and Shanghai had the largest growth in impervious areas. Spatially and temporally quantifying the change in urban impervious areas can help to better understand the intensity of urbanization in a region. Therefore, quantifying the change in urban impervious area has an important role in the study of regional environmental and economic development, policy formulation, and the rational use of resources in both time and space.<\/jats:p>","DOI":"10.3390\/ijgi8010031","type":"journal-article","created":{"date-parts":[[2019,1,16]],"date-time":"2019-01-16T03:09:13Z","timestamp":1547608153000},"page":"31","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Spatial\u2013Temporal Evolution and Regional Differentiation Features of Urbanization in China from 2003 to 2013"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1825-7771","authenticated-orcid":false,"given":"Peiyu","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longtao","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department Computational Landscape Ecology, Helmholtz Centre for Environmental Research\u2014UFZ, Permoserstr. 15, D-04318 Leipzig, Germany"},{"name":"Lab for Landscape Ecology, Department of Geography, Humboldt University of Berlin, Rudower Chaussee 16, 12489 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Bai","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanxiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1080\/01944369608975688","article-title":"Impervious Surface Coverage: The Emergence of a Key Environmental Indicator","volume":"62","author":"Arnold","year":"1996","journal-title":"J. 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