{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T17:49:33Z","timestamp":1784051373533,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,20]],"date-time":"2020-06-20T00:00:00Z","timestamp":1592611200000},"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>Detailed urban land use information is the prerequisite and foundation for implementing urban land policies and urban land development, and is of great importance for solving urban problems, assisting scientific and rational urban planning. The existing results of urban land use mapping have shortcomings in terms of accuracy or recognition scale, and it is difficult to meet the needs of fine urban management and smart city construction. This study aims to explore approaches that mapping urban land use based on multi-source data, to meet the needs of obtaining detailed land use information and, taking Lanzhou as an example, based on the previous study, we proposed a process of urban land use classification based on multi-source data. A combination road network dataset of Gaode and OpenStreetMap (OSM) was synthetically applied to divide urban parcels, while multi-source features using Sentinel-2A images, Sentinel-1A polarization data, night light data, point of interest (POI) data and other data. Simultaneously, a set of comparative experiments were designed to evaluate the contribution and impact of different features. The results showed that: (1) the combination utilization of Gaode and OSM road network could improve the classification results effectively. Specifically, the overall accuracy and kappa coefficient are 83.75% and 0.77 separately for level I and the accuracy of each type reaches more than 70% for level II; (2) the synthetic application of multi-source features is conducive to the improvement of urban land use classification; (3) Internet data, such as point of interest (POI) information and multi-time population information, contribute the most to urban land use mapping. Compared with single-moment population information, the multi-time population distribution makes more contributions to urban land use. The framework developed herein and the results derived therefrom may assist other cities in the detailed mapping and refined management of urban land use.<\/jats:p>","DOI":"10.3390\/rs12121987","type":"journal-article","created":{"date-parts":[[2020,6,23]],"date-time":"2020-06-23T09:05:33Z","timestamp":1592903133000},"page":"1987","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Detailed Mapping of Urban Land Use Based on Multi-Source Data: A Case Study of Lanzhou"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9460-941X","authenticated-orcid":false,"given":"Leli","family":"Zong","sequence":"first","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sijia","family":"He","sequence":"additional","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiting","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Economic and Trade, Hebei GEO University, Shijiazhuang 050031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Bie","sequence":"additional","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"},{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyun","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"},{"name":"The Key Laboratory of Western China\u2019s Environmental Systems, Ministry of Education (MOE), Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingru","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaowen","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China"},{"name":"The Key Laboratory of Western China\u2019s Environmental Systems, Ministry of Education (MOE), Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1126\/science.1245200","article-title":"The Hidden Geometry of Complex, Network-Driven Contagion Phenomena","volume":"342","author":"Brockmann","year":"2013","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1038\/nature10452","article-title":"Solutions for a cultivated planet","volume":"478","author":"Foley","year":"2011","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1641\/0006-3568(2002)052[0883:UBAC]2.0.CO;2","article-title":"Urbanization, Biodiversity, and Conservation","volume":"52","author":"McKinney","year":"2002","journal-title":"BioScience"},{"key":"ref_4","first-page":"351","article-title":"Methodology for classifying and detecting intra-urban land use change: A case study of Changchun city during the last 100 years","volume":"14","author":"Kuang","year":"2010","journal-title":"J. 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