Evaluating Urban Land Resource Carrying Capacity With Geographically Weighted Principal Component Analysis - A Case Study in Wuhan, China

A - Papers appearing in refereed journals

Lu, B., Shi, Y., Qin, S., Yue, P., Zheng, J. and Harris, P. 2024. Evaluating Urban Land Resource Carrying Capacity With Geographically Weighted Principal Component Analysis - A Case Study in Wuhan, China. Transactions in GIS. https://doi.org/10.1111/tgis.13241

AuthorsLu, B., Shi, Y., Qin, S., Yue, P., Zheng, J. and Harris, P.
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.

KeywordsAHP ; Geographic census data; Spatial heterogeneity; Multiscale; GWPCA
Year of Publication2024
JournalTransactions in GIS
Digital Object Identifier (DOI)https://doi.org/10.1111/tgis.13241
Web address (URL)https://onlinelibrary.wiley.com/doi/abs/10.1111/tgis.13241
Open accessPublished as green open access
FunderBiotechnology and Biological Sciences Research Council
National Natural Science Foundation of China
Funder project or codeResilient Farming Futures (WP3): Digital platforms for supporting national agroecosystem ‘resilience’ through systems adaptations
Publisher's version
Copyright license
CC BY
Accepted author manuscript
Copyright license
CC BY
Supplemental file
Copyright license
CC BY
Output statusPublished
Publication dates
Online03 Sep 2024
Publication process dates
Accepted16 Aug 2024
PublisherWiley
ISSN1361-1682

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