{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T20:25:05Z","timestamp":1775161505625,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T00:00:00Z","timestamp":1637625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As the basic spatial unit of urban planning and management, it is necessary to understand the real development trend of urban functional zones in time and carry out reasonable planning adjustment. Because of the complexity of urban functional zones, the automatic recognition of urban functional zones has become a significant scientific problem in urban research. Urban functional zones contain natural and socioeconomic characteristics, but the existing identification methods fail to comprehensively consider these features. This paper proposes a framework that integrates multisource geographic data to recognize urban functional zone. We used high-resolution remote sensing imagery, point-of-interest (POI) data and high-spatial-resolution nighttime light imagery to extract both natural and socioeconomic features for urban functional zone accurate interpretation. Various features provide more accurate and comprehensive description for complex urban functional zone, so as to improve the recognition accuracy of urban functional zone. At present, there are few studies on urban functional zone recognition based on the combination of high-resolution remote sensing image, POI and high-resolution nighttime light imagery. The application potential of the combination of these three geographical data sources in urban function zone recognition needs to be explored. The experimental results show that the accuracy of urban functional zone recognition was obviously improved by the three data sources combination, the overall accuracy reached 80.30% and a comprehensive evaluation index reached 68.26%. This illustrate that the combination of the three data sources is beneficial to the urban functional zone recognition.<\/jats:p>","DOI":"10.3390\/rs13234732","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"4732","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Urban Functional Zone Recognition Integrating Multisource Geographic Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Siya","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China"},{"name":"Urban Remote Sensing Application Innovation Center, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China"}]},{"given":"Hongyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China"},{"name":"Urban Remote Sensing Application Innovation Center, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China"}]},{"given":"Hangxing","family":"Yang","sequence":"additional","affiliation":[{"name":"Changchun Automobile Industry Institute, Changchun 130011, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1080\/13658816.2016.1244608","article-title":"Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model","volume":"31","author":"Yao","year":"2017","journal-title":"Int. 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