Paper
5 November 2008 The spatial relationship analysis of regional development potential and resource and environment carrying capacity in China
Yan Zhang, Jianhua Xu, Gang Zeng, Qi Shen, Qing Hu
Author Affiliations +
Proceedings Volume 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics; 714413 (2008) https://doi.org/10.1117/12.812734
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
The main goal in this study is to explore the spatial relationship of Chinese regional development potential (DP) and resource & environment carrying capacity (REC) in 2000 and 2006 by using meta-synthesis of spatial statistical analysis and GIS technique. The results show that: The spatial distribution trend of DP and REC are overall gradient descending from coastal to inland, then to the western provinces. They all demonstrate that spatial agglomeration with global significant, namely high-DP regions aggregated in the east, low-DP regions aggregated in the west. The high-REC of central, eastern and southern China are improved and aggregated, but the low-REC aggregated in northwest. Chinese regional DP and REC are divided into five different kinds of regions based on the results of k-means clustering analysis and spatial clustering, which demonstrate that each area's DP and REC's spatial association measure is not very obviously. Compared to the high-DP region, the low-DP region is more restricted to the REC.
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Yan Zhang, Jianhua Xu, Gang Zeng, Qi Shen, and Qing Hu "The spatial relationship analysis of regional development potential and resource and environment carrying capacity in China", Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 714413 (5 November 2008); https://doi.org/10.1117/12.812734
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Cited by 2 scholarly publications.
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KEYWORDS
Statistical analysis

Geographic information systems

Analytical research

Geography

Statistical methods

Lithium

Pollution

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