期刊论文

Chong Huang

英文

Remote Sensing

2072-4292

2022

14

17

4201-

10.3390/rs14174201

Conceptualization, C.H. and L.R.; methodology, C.X. and C.H.; software, C.X.; validation, C.X., C.H. and L.R.; formal analysis, C.H.; investigation, C.H.; re-sources, C.H. and L.R.; data curation, C.X.; writing—original draft preparation, C.X.; writing—review and editing, C.H. and L.R.; visualization, C.X.; supervision, L.R.; funding acquisition, C.H. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China grant number (41890854).

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Accurately identifying and delineating urban functional areas has seen increasing demand in smart urban planning, landscape design, and resource allocation. Recently, POI (point of interest) data have been increasingly applied to identify urban functional areas. However, heterogeneity in urban spaces or the corresponding POI data has not been fully considered in previous studies. In this study, we proposed a new scheme for urban-functional-area identification by combining POI data, OpenStreetMap (OSM) datasets, and high-resolution remote-sensing imagery. A function-intensity index that integra...