Ecological environment assessment, which forms the basis for the survival and development of human society, is a crucial measure for the sustainable development of society and economy. However, current quantitative assessment models such as EI, EQI, RSEI et al. are insufficient to meet the requirements of dynamic research in large areas, long time series and dense time intervals. Therefore, in this paper, we constructed the comprehensive ecological environment quality index model SCEQI that can meet these needs by applying the remote sensing big data as the data source. The SCEQI aggregated the ecological indices NDVI, NDBSI, Lst and Wet by full-sequence dynamic dimensionless, automated principal component analysis and multi-temporal average method. In order to verify the spatial and temporal accuracy of the model, we took Henan Province as an example to compare the result of SCEQI with that of EI, EQI, RSEI and proved that SCEQI performed better in both time and space. Also, we verified the superiority of time, space, and precision of SCEQI with profiles, samples, and cluster analysis.
Keywords: ecological environment quality; spatial accuracy; temporal accuracy.