Developing an Enhanced Ecological Evaluation Index (EEEI) Based on Remotely Sensed Data and Assessing Spatiotemporal Ecological Quality in Guangdong–Hong Kong–Macau Greater Bay Area, China

Ecological changes affected by increasing human activities have highlighted the importance of ecological quality assessments. An appropriate and efficient selection parameters is fundamental for On basis remote sensing data methods, this study developed an enhanced evaluation index (EEEI) with five integrated containing pixel sub-pixel information: normalized difference vegetation index, impervious surface coverage, soil land temperature, wetness component tasseled cap transformation. Significantly, EEEI simultaneously considered aspects conditions (i.e., greenness, activities, dryness, heat, moisture), which provided effective guide systematic parameters. The has a clear theoretical framework, all can be obtained quickly on datasets suitable promotion application assessments to various areas scales. Furthermore, was applied assess detect Guangdong–Hong Kong–Macau Greater Bay Area (GBA) China. Assessment results indicated that GBA currently facing great challenges degradation trend from 2000 2020, emphasizes significance urgency eco-environmental protection GBA. This evidence used as scientific, objective, quantitative, comprehensive assessment, also aid regional environmental management protection.