Analysis of changes in the spatiotemporal characteristics of impervious surfaces and their influencing factors in the Central Plains Urban Agglomeration of China from 2000 to 2018

Chunhong Zhao; Huabo Zhang; Haiying Wang; Jinyi Zhao

doi:10.1016/j.heliyon.2023.e18849

Analysis of changes in the spatiotemporal characteristics of impervious surfaces and their influencing factors in the Central Plains Urban Agglomeration of China from 2000 to 2018

Heliyon. 2023 Aug 1;9(8):e18849. doi: 10.1016/j.heliyon.2023.e18849. eCollection 2023 Aug.

Authors

Chunhong Zhao^{1

2}, Huabo Zhang^{1

2}, Haiying Wang^{1

2

3}, Jinyi Zhao^{1

2}

Affiliations

¹ The College of Geography and Environment Science, Henan University, Kaifeng, 475004, China.
² Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Kaifeng, 475004, China.
³ Institute of Urban Big Data, Henan University, Kaifeng, 475004, China.

Abstract

The change of the impervious surface area (ISA) is an important feature of urban spatial expansion. Understanding the spatial and temporal change characteristics of urban impervious surfaces and their influencing factors is of great significance to the planning, management, and urbanization development of cities. This paper adopts a global artificial impervious surface dataset, with a resolution of 30 m, calculates and processes the data based on the ArcGIS platform, adopts the MK trend test method, introduces the dynamic degree, qualitatively and quantitatively analyses the changing characteristics of the ISA in the Central Plains Urban Agglomeration (CPUA), and analyzes the influencing factors of ISA changes using GeoDetector. The results show that the ISA dynamic degree was significantly enhanced from 2000 to 2018, which increased 1.86 times, indicating the accelerated outward expansion of the CPUA and the rapid level of urban development during that period. The explanatory power of the greenery coverage area on the change of the ISA in the CPUA during 2000-2018 was the strongest; the same factor has different explanatory powers for the ISA in different periods. The influencing factors have an enhanced relationship between two and two, including two-factor enhancement and nonlinear enhancement, in 2000-2009, during which the interaction level of the greenery coverage area and the GDP per capita was strong, while from 2009 to 2018, the interaction between transportation and other factors was significantly strong.

Keywords: Central Plains Urban Agglomeration; GeoDetector; Impervious surface area; Spatiotemporal feature change.