[Ecological Quality Assessment and Driving Analysis of Jiangle County Based on Modified Remote Sensing Ecological...

The RSEI index has been used widely in ecological environment quality assessment， but its application in high vegetation coverage areas in southern China remains relatively limited. To monitor and evaluate the ecological environment quality in the region more effectively， indices of humidity （WET）， heat （LST）， and dryness （NDBSI） factors and the comprehensive vegetation index mNDVI were introduced to construct the modified remote sensing ecological index （MRSEI） by principal component analysis. Then， the GEE cloud platform and ArcGIS 10.8 platform were used to analyze the spatial and temporal distribution and driving mechanisms of ecological quality in Jiangle County from 2000 to 2020. The results were as follows： ① Compared with RSEI， the average correlation between MRSEI and the principal components was higher. In the three experimental areas， its contrast was increased by 10.538， 2.923， and 8.558， and its entropy was increased by 0.024， 0.046， and 0.025， respectively. ② The overall change of MRSEI in Jiangle County was an increase， with an average annual increment of 0.010. Areas with good ecological quality accounted for the largest proportion of the county， ranging from 33.61% to 38.28%， while the proportion of county areas classified as poor or poorer was about 10%. The proportion of areas defined as stable in ecological change ranged from 42.23% to 59.05%， although this fluctuated significantly from year to year. Moreover， the ecological environment was more prone to deterioration in the southwest and northern regions， and urban construction expanded outward from the central areas. Through the 20 years， the land area with improved ecological quality reached 424.34 km²， indicating a significant improvement in Jiangle County's ecological environment. ③ Land use type and slope were the primary factors influencing spatial variations in ecological environment quality， with annual average precipitation also playing a significant role. The interactions among driving factors led to some degree of improvement， with the interaction between land use type and annual average precipitation having the strongest influence on MRSEI spatial differentiation， contributing 36.1% to the variation. This study provides a scientific basis for ecological environment monitoring and sustainable development in Jiangle County.