Dynamic monitoring of ecological environment quality in Lijiang River Basin based on RSEI
WEI Yuhan1, QIAN Jianping1, FAN Weiwei2, LI Peng1
1. Department of Earth Sciences, Guilin University of Technology, 541006, Guilin, Guangxi, China; 2. College of Engineering & Technology, Northeast Forestry University, 150040, Harbin, China
Abstract：[Background] The topography and geomorphology of Lijiang River Basin is complex and the basin area is wide. It is of great reference value to understand the ecological environment quality and changes of Lijiang River Basin for environmental protection. [Methods] In order to quickly and accurately obtain the ecological environment of Lijiang River Basin, the Landsat series of remote sensing images in the Lijiang River Basin in 1991, 2001, 2009 and 2019 were used to extract the Remote Sensing Ecological Index (RSEI) using principal component analysis. Multiple regression analysis was performed with the four index factors of greenness, humidity, dryness and heat. The correlation analysis between the change of RSEI index and the change of vegetation coverage has achieved the dynamic remote sensing dynamic monitoring of the ecological environment quality in the Lijiang River Basin in the past 30 years. [Results] The average values of RSEI in Lijiang River Basin in 1991, 2001, 2009, and 2019 were 0.534, 0.530, 0.662, and 0.625. In the past 30 years, the overall ecological environment quality has changed from "medium" to "good", and the overall ecology "better" area has reached 2 707.809 km2, mainly concentrated in the central and southern regions. The most obvious improvement period was from 2001 to 2009, in this period, the ecological area of "getting better" category reached 3 933.274 km2. The regression model analysis of the four index factors of greenness, humidity, heat and dryness and RSEI index showed that the four index factors all had important effects on the ecological environment quality of the Lijiang River Basin, among which the greenness index had the greatest impact and the humidity index had the least influential. Among the four index factors, the positive correlation between greenness and humidity and the RSEI index promoted the improvement of ecological environment quality, and the dryness and heat had a negative correlation with the RSEI index, which had an inhibitory effect on the improvement of the ecological environment. The four-year regression model coefficient showed that the index coefficient of dryness increased year by year, and the regression model coefficient of heat in 2019 reached 0.628. This indicated that the soil water content of the Lijiang River Basin was decreasing and the soil has a tendency to dry, and the 2019 heat index and dryness index were related to the Lijiang River. The comprehensive impact degree of the river basin ecological environment was greater than the greenness and humidity indicators. Through the three-gradient method, it is found that the regression coefficient R2 of the vegetation coverage change and the RSEI index in the whole period from 1991 to 2019 reached 0.890, showing a significant and positive linear correlation. [Conclusions] RSEI index can objectively mirror the dynamic changes of eco-environmental quality in Lijiang River Basin and provide decision support for regional eco-environmental quality.
魏雨涵, 钱建平, 范伟伟, 李彭. 基于RSEI的漓江流域生态环境质量动态监测[J]. 中国水土保持科学, 2021, 19(1): 122-131.
WEI Yuhan, QIAN Jianping, FAN Weiwei, LI Peng. Dynamic monitoring of ecological environment quality in Lijiang River Basin based on RSEI. SSWC, 2021, 19(1): 122-131.
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2021, Vol. 19 
