Impacting Factors and Temporal and Spatial Differentiation of Land Subsidence in Shanghai

Yishao Shi, Donghui Shi and Xiangyang Cao
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Yishao Shi: College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
Donghui Shi: College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
Xiangyang Cao: College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China

Sustainability, 2018, vol. 10, issue 9, 1-18

Abstract: This paper uses Grey Correlation Degree Analysis (GCDA) to obtain and compare the relationships between major impacting factors and land subsidence, and finds the spatial characteristics of subsidence in the urban centre by Exploratory Spatial Data Analysis (ESDA). The results show the following: (1) Annual ground subsidence in Shanghai has occurred in four stages: slow growth in the 1980s, rapid growth in the 1990s, gradual decline in the first decade of the 21st century, and steady development currently. (2) In general, natural impact factors on land subsidence are more significant than social factors. Sea-level rise has the most impact among the natural factors, and permanent residents have the most impact among the social factors. (3) The average annual subsidence of the urban centre has undergone the following stages: “weak spatial autocorrelation” → “strong spatial autocorrelation” → “weak spatial autocorrelation”. (4) The “high clustering” spatial pattern in 1978 gradually disintegrated. There has been no obvious spatial clustering since 2000, and the spatial distribution of subsidence tends to be discrete and random.

Keywords: land subsidence; natural factors; social factors; spatial distribution; clustering pattern (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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