remote sensing Article Research on Urban Carrying Capacity Based on Multisource Data Fusion—A Case Study of Shanghai Xiangyang Cao 1, Yishao Shi 2,* and Liangliang Zhou 2 1 School of Civil Engineering, Shandong Jiaotong University, Ji’nan 250357, China;
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[email protected] Abstract: Taking Shanghai as an example, this paper uses remote sensing (RS) and geographical information systems (GIS) technology to conduct multisource data fusion and a spatial pattern analysis of urban carrying capacity at the micro scale. The main conclusions are as follows: (1) based on the “production, living and ecology” land functions framework and land use data, Shanghai is divided into seven types of urban spaces to reveal their heterogeneity and compatibility in terms of land use functions. (2) We propose an urban carrying capacity coupling model (UCCCM) based on multisource data. The model incorporates threshold and saturation effects, which improve its power to explain urban carrying capacity. (3) Using the exploratory spatial data analysis (ESDA) technique, this paper studies the spatial pattern of carrying capacity in different urban spaces of Shanghai. (4) We analyse the causes of the cold spots in each urban space and propose strategies to improve the urban carrying capacity according to local conditions. Keywords: urban carrying capacity; spatial heterogeneity; multisource data fusion; ESDA Citation: Cao, X.; Shi, Y.; Zhou, L. Research on Urban Carrying Capacity Based on Multisource Data 1. Introduction Fusion—A Case Study of Shanghai. Rapid urbanization and expanding demand for resources and services are exerting Remote Sens.