{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T15:43:05Z","timestamp":1777909385586,"version":"3.51.4"},"reference-count":63,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T00:00:00Z","timestamp":1623801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41872249"],"award-info":[{"award-number":["41872249"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key R&amp;D Program of China","award":["2019YFC1805905"],"award-info":[{"award-number":["2019YFC1805905"]}]},{"name":"the Fundamental Research Funds for the Central Universities of Central South University","award":["2020zzts675"],"award-info":[{"award-number":["2020zzts675"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Urban area hotspots are considered to be an ideal proxy for spatial heterogeneity of human activity, which is vulnerable to urban expansion. Nighttime light (NTL) images have been extensively employed in monitoring current urbanization dynamics. However, the existing studies related to NTL images mainly concern detection of urban areas, leaving inner spatial differences in urban NTL luminosity poorly explored. In this study, we propose an innovative approach to explore the spatiotemporal trajectory of urban area hotspots using monthly Visible Infrared Imaging Radiometer Suite (VIIRS) NTL images. Firstly, multi-temporal VIIRS NTL intensity was decomposed by time-series analysis to obtain annual stable components after data preprocessing. Secondly, the support vector machine (SVM) regression model was utilized to identify urban area hotspots. In order to ensure the model accuracy, the grid search and cross-validation method was integrated to achieve the optimized model parameters. Finally, we analyzed the spatiotemporal migration trajectory of urban area hotspots by the center of gravity method (i.e., shift distance and angle of urban area hotspot centroid). The results indicate that our method successfully captured urban area hotspots with a regression coefficient over 0.8. Meanwhile, the findings give an intuitive understanding of coupling interaction between urban area hotspots and socioeconomic indicators. This study provides important insights for further decision-making regarding sustainable urban planning.<\/jats:p>","DOI":"10.3390\/ijgi10060415","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T10:27:07Z","timestamp":1623839227000},"page":"415","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Monitoring the Spatiotemporal Trajectory of Urban Area Hotspots Using the SVM Regression Method Based on NPP-VIIRS Imagery"],"prefix":"10.3390","volume":"10","author":[{"given":"Yuling","family":"Ruan","sequence":"first","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhong","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghui","family":"Chen","sequence":"additional","affiliation":[{"name":"Dongguan Geographic Information & Urban Planning Research Center, Dongguan 523129, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingya","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.techsoc.2005.10.005","article-title":"Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability","volume":"28","author":"Cohen","year":"2006","journal-title":"Technol. 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