The classification of urban functional areas plays an important role in urban planning and resource management. Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature (LST) characteristics, these two types of characteristics have rarely been fully integrated and used for functional area classification. In this paper, a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features. First, metrics are constructed from three levels, namely, building, road and region, which are used to portray urban morphology; LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics: the average temperature, maximum temperature, temperature difference and standard deviation of temperature. Then, the functional areas are classified into four categories:service/public land, commercial land, residential land and industrial land. A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas. The effectiveness of the proposed framework is tested in the study area of Shenzhen City, Guangdong Province. The results show that the combined classification accuracy of the proposed classification method is 0.85, which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features. The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.

Bin Li;Yefei Liu;Hanfa Xing;Yuan Meng;Guang Yang;Xiaoding Liu;Yaolong Zhao

College of Geography and Environment,Shandong Normal University,Jinan,China;Beidou Research Institute,Faculty Of Engineering,South China Normal University,FoShan,China;School of Geography,South China Normal University,Guangzhou,China;Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China,Ministry of Natural Resources,Guangzhou,China;Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University,Hong Kong,China;Institute of Surveying and Mapping,Department of Natural Resources of Guangdong Province,Guangzhou,China

地球空间信息科学学报（英文版）

[1]Bin Li;Yefei Liu;Hanfa Xing;Yuan Meng;Guang Yang;Xiaoding Liu;Yaolong Zhao-.Integrating urban morphology and land surface temperature characteristics for urban functional area classification)[J].地球空间信息科学学报（英文版）,2022(02):337-352

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