Evaluation of Urban Intensive Land Use Degree with GEE Support: A Case Study in the Pearl River Delta Region, China

Yiqun Shang, Dongya Liu () and Yi Chen
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Yiqun Shang: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China
Dongya Liu: School of Information Engineering, China University of Geosciences, Beijing 100083, China
Yi Chen: School of Accounting, Shandong University of Finance and Economics, Jinan 250014, China

Sustainability, 2022, vol. 14, issue 20, 1-15

Abstract: Evaluation of intensive land use (ILU) over long time series is essential for the rational use of land and urban development. We propose a novel framework for analyzing ILU in the Pearl River Delta (PRD) region of China. First, we used Google Earth Engine (GEE) to obtain cities’ built-up land information. Second, we calculated the ILU degree and constructed an evaluation index system based on the Pressure–State–Response (PSR) theoretical framework. Third, we employed Geodetector to determine the dominant influencing factors on ILU. The findings are as follows: (1) It is accurate and effective to extract land use data using GEE. From 2000 to 2020, all cities’ built-up areas increased, but the increases differed by city. (2) While the ILU level in all cities has increased over the past 20 years, the ILU level in each city varies. Specifically, Shenzhen had the highest ILU degree in 2020, followed by core cities such as Guangzhou, Dongguan, and Zhuhai, while cities on the PRD region’s periphery, such as Zhaoqing and Jiangmen, had relatively low ILU levels. (3) In terms of time, the dominant factors influencing ILU in the PRD region have shifted over the past two decades. During this period, however, two factors (economic density and disposable income per capita) have always played a dominant role. This suggests that improving economic output efficiency and the city’s economic strength is a feasible way to raise the ILU level at this time.

Keywords: intensive land use (ILU) degree; Google Earth Engine (GEE); Pressure–State–Response (PSR) theoretical framework; Geodetector; Pearl River Delta (PRD) region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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