Exploring the Spatial Pattern and Influencing Factors of Land Carrying Capacity in Wuhan

Nana Yang, Jiansong Li, Binbin Lu, Minghai Luo and Linze Li
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Nana Yang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Jiansong Li: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Binbin Lu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Minghai Luo: Monitoring of Wuhan Geographical Conditions group in Wuhan Geomatics Institute, Wuhan 430079, China
Linze Li: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Sustainability, 2019, vol. 11, issue 10, 1-16

Abstract: Land carrying capacity is an important factor for urban sustainable development. It provides essential insights into land resource allocation and management. In this article, we propose a framework to evaluate land carrying capacity with multiple data sources from the first geographical census and socioeconomic statistics. In particular, an index, Land Resource Pressure ( LRP ), is proposed to evaluate the land carrying capacity, and a case study was carried out in Wuhan. The LRP of Wuhan was calculated on 250 m * 250 m grids, and showed a circularly declining pattern from central to outer areas. We collected its influencing factors in terms of nature resources, economy, transportation and urban construction, and then analyzed its causes via geographically weighted (GW) models. Firstly, pair-wise correlations between LRP and each influencing factor were explored via the GW correlation coefficients. These local estimates provide an important precursor for the following quantitative analysis via the GW regression (GWR) technique. The GWR coefficient estimates interpret the influences on LRP in a localized view. Results show that per capita gross domestic product (PerGDP ) showed a higher absolute estimate among all factors, which proves that PerGDP has a relieving effect on LRP , especially in the southwestern areas. Overall, this study provides a technical framework to evaluate land carrying capacity with multi-source data sets and explore its localized influences via GW models, which could provide practical guidance for similar studies in other cities.

Keywords: sustainable development; geographic census; land carrying capacity; population; geographically weighted regression; spatial heterogeneity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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