Habitat Quality Assessment and Driving Factors Analysis of Guangdong Province, China

Yongxin Liu, Yiting Wang, Yiwen Lin, Xiaoqing Ma, Shifa Guo, Qianru Ouyang and Caige Sun ()
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Yongxin Liu: School of Geography, South China Normal University, Guangzhou 510631, China
Yiting Wang: School of Geography, South China Normal University, Guangzhou 510631, China
Yiwen Lin: School of Geography, South China Normal University, Guangzhou 510631, China
Xiaoqing Ma: School of Geography, South China Normal University, Guangzhou 510631, China
Shifa Guo: School of Geography, South China Normal University, Guangzhou 510631, China
Qianru Ouyang: School of Geography, South China Normal University, Guangzhou 510631, China
Caige Sun: School of Geography, South China Normal University, Guangzhou 510631, China

Sustainability, 2023, vol. 15, issue 15, 1-23

Abstract: Habitat quality is a key factor in regional ecological restoration and green development. However, limited information is available to broadly understand the role of natural and human factors in influencing habitat quality and the extent of their impact. Based on remote sensing monitoring data of land use over five time points (2000, 2005, 2010, 2015, and 2020), natural factors, and socioeconomic data, we applied the InVEST model to assess habitat quality in Guangdong Province. Using a multiscale geographically weighted regression (MGWR) model, we explored the spatial scale differences in the role of natural and human factors affecting habitat quality and the degree of their influence. The highlights of the results are as follows: ① From 2000 to 2020, land-use changes in the Pearl River Delta (PRD) region were particularly obvious, with the dynamic degree of construction land being higher than that of other land-use types. Construction land has gradually occupied agricultural and ecological land, causing damage to habitats. ② The overall habitat quality in Guangdong Province is decreasing; the areas with low habitat quality values are concentrated in the PRD region and the coastal areas of Chaoshan, Maoming, and Zhanjiang, while the areas with higher habitat quality values are mainly located in the non-coastal areas in the east and west of Guangdong and the north of Guangdong. ③ The MGWR regression results showed that the normalized vegetation index had the strongest effect on habitat quality, followed by road density, gross domestic product (GDP) per unit area, slope, and average elevation, and the weakest effect on average annual precipitation. ④ The effects of average elevation, GDP per unit area, and normalized vegetation index on habitat quality were significantly positively correlated, while road density was significantly negatively correlated. These results provide a scientific basis for adjusting spatial land-use planning and maintaining regional ecological security.

Keywords: habitat quality; InVEST; MGWR; influencing factors; ecosystem (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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