Evaluating Urban Land Resource Carrying Capacity With Geographically Weighted Principal Component Analysis: A Case Study in Wuhan, China
Binbin Lu
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, UK
Search for more papers by this authorYilin Shi
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
School of Computer Science, Wuhan University, Wuhan, China
Search for more papers by this authorPeng Yue
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Search for more papers by this authorCorresponding Author
Jianghua Zheng
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
Correspondence:
Jianghua Zheng ([email protected])
Search for more papers by this authorPaul Harris
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, UK
Search for more papers by this authorBinbin Lu
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, UK
Search for more papers by this authorYilin Shi
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
School of Computer Science, Wuhan University, Wuhan, China
Search for more papers by this authorPeng Yue
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Search for more papers by this authorCorresponding Author
Jianghua Zheng
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China
Correspondence:
Jianghua Zheng ([email protected])
Search for more papers by this authorPaul Harris
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, UK
Search for more papers by this authorFunding: This work was supported by National Natural Science Foundation of China (Grant 42071368) and the Fundamental Research Funds for the Central Universities, China (Grants 2042022dx0001 and 2042024kf0005).
ABSTRACT
With the rapid urbanization in China, urban land resources gradually become the core of urban development. This study spatially evaluated the urban land resource carrying capacity (LRCC) with a case study of the built-up area in Wuhan from 2015 to 2020. Following an evaluation index system, five critical LRCC indicators, including population density, GDP per land area, plot ratio, building density, and road network density, were selected by an analytical hierarchical process. The synthesis of indicators, however, is usually challengeable due to homogeneous assumptions of traditional techniques. In this study, we adopted a local technique, geographically weighted principal component analysis, to calculate a comprehensive carrying pressure (CCP) concerning spatially varying contributions of each indicator on their synthesis across different geographic locations. On mapping these spatial outputs of the built-up area in Wuhan, the highest CCP was found in the central areas, where population size tends to be influential and the dominant variable in 62.69% of subdistricts. Furthermore, increased construction over the 5 years has led to an increased CCP in some of the peripheries of the built-up area, and 55.22% of subdistricts show rising changes. With the GWPCA technique, this framework works well in evaluating and analyzing urban LRCC from a new local perspective.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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