关键词: 生态环境指数, 时空大数据, 遥感反演, 主成分分析法

Abstract: To address the limitations of existing ecological indices that often neglect water bodies and are inadequate for comprehensive regional assessment.This study develops an improved remote sensing ecological index (MRSEI)by integrated multi-source spatio-temporal data.The model incorporates five indicators—NDVI,NDBSI,TVDI,EWI,and TWI—to evaluate ecological conditions from four dimensions: greenness,dryness,wetness,and water.An empirical analysis is conducted using 2023 Landsat-8 imagery in Peixian county,Jiangsu province.The results indicate that the ecological environment in the study area had generally improved,with significant enhancements observed in three western towns and eastern lakeside regions.Compared to the traditional RSEI,the MRSEI demonstrates higher accuracy in evaluating water bodies (with a approximately 12% increase in correlation coefficient),owing to its incorporation of water-related indicators and optimized weighting.This study provides an effective tool for accurate ecological quality assessment and sustainable management at the county level,and more suitable for precise monitoring of large-scale land-water composite ecosystems.

Key words: MRSEI, spatio-temporal big data, remote sensing inversion, PCA