Spatial-temporal evolution and motivation of ecological vulnerability based on RSEI and GEE in the Jianghan Plain from 2000 to 2020

Abstract

Recent urbanization and growing food consumption have had a severely detrimental effect on the ecological environment of the Jianghan Plain. The ecological fragility of the Jianghan Plain must be continually monitored for environmental conservation and sustainable development. This study utilized principal component analysis (PCA) to quantitatively assess the ecological vulnerability of the Jianghan Plain based on the remote sensing ecological index (RSEI) and analyzed the space-time changes and drivers in the Jianghan Plain from 2000 to 2020 using the Google Earth Engine Platform (GEE). The findings of this research indicated that the ecological vulnerability of the Jianghan Plain from 2000 to 2020 was predominantly Moderate or Strong level. But still, the EVI displayed a changing decreasing trend, revealing a small development towards a healthier ecological environment. The most significant ecological vulnerability deterioration occurred between 2005 and 2010, accounting for roughly 44.90 percent, whereas the highest improvement occurred between 2000 and 2005, occupying approximately 37.52% of the area. Moran’s I of EVI was greater than 0 in Jianghan Plain and displayed a growing and subsequently a falling trend, representing that the spatial distribution of regional ecological vulnerability was strongly correlated and aggregated and that the degree of aggregation has declined. The effects of heat, greenness, wetness, and dryness on the ecological vulnerability of Jianghan Plain were all significant, with greenness and wetness being the primary determinants of the change in Jianghan Plain’s ecological vulnerability. The results of this study can offer a theoretical and scientific foundation for ecological protection and restoration in the Jianghan Plain. Meanwhile, this study also provides a practical and rapid method for monitoring regional ecological vulnerability using RSEI, GEE, and PCA, which can be applied elsewhere for ecological vulnerability evaluation.