Abstract
Ecological environment quality and resilience assessment is an important prerequisite for ensuring the coordination and stability of socio-economic development and eco-environment protection. Remote sensing technology has provided new approaches for quantitatively evaluating regional ecological environment quality and resilience rapidly, accurately, and objectively. Taking the middle and lower reaches of the Yangtze River Economic Belt (YREBML) as an example, to assess ecological environment quality, this study calculated the remote sensing ecological index (RSEI) based on the Google Earth Engine using Moderate Resolution Imaging Spectroradiometer (MODIS) data with a spatial resolution of 500 m during 2000–2020. An evaluation index to assess ecological resilience and its spatial pattern based on the RSEI of 2000–2020 was then constructed. The evaluation index was constructed from two dimensions, including the sensitivity and adaptability of the RSEI. Finally, this study identified key factors that affect ecological residence based on a structural equation model. The results showed that the overall RSEI was at moderate and good levels in the YREBML during 2000–2020, accounting for more than 85% of the total area. Its spatial characteristics showed that the RSEI was higher in the middle reaches than in the lower reaches of the YREB, and higher in the south than in the north. The overall RSEI in the YREBML showed a decreasing trend during 2000–2020, with 54.36% of the region improving and 45.64% declining. Areas with declining RSEI were concentrated in Anhui, while the increasing RSEI was observed in Zhejiang. In addition, the spatial pattern of ecological resilience was characterized by high resilience in the north and east, and low resilience in the south and west. High resilience areas accounted for 40.48% of the YREBML, mainly contributed by Jiangxi and Hunan provinces. The driving factors analysis results indicated that economic development, natural disaster risk, and environmental pollution would further affect ecological resilience of urban systems. This study provides more scientific and effective data support for ecological environment monitoring and governance.
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