Journal of Ecology and Rural Environment ›› 2023, Vol. 39 ›› Issue (7): 853-863.doi: 10.19741/j.issn.1673-4831.2022.1054

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Assessment of Ecological Environment Quality in Qilian Mountain National Nature Reserve Based on Improved RSEI Model

WANG Xiao-xian1,2, ZHANG Xiu-xia1,2, LI Wang-ping1,2, CHENG Xiao-qiang1,2, LING Qing1,2, ZHOU Zhao-ye1,2, HAO Jun-ming1,2, LIN Qing-run1,2, CHEN Lu1,2   

  1. 1. School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
    2. Lanzhou University of Technology/Gansu Province Emergency Mapping Engineering Research Center, Lanzhou 730050, China
  • Received:2022-10-10 Online:2023-07-25 Published:2023-07-19

Abstract: Aiming at the non uniqueness of feature vector direction of remote sensing ecological index(RSEI) model and the existence of necrotic pixels in optical images, 489 Landsat TM/SR availability remote sensing images of Qilian Mountain National Nature Reserve from 1986 to 2021 were selected in view of Google Earth Engine platform, and the improved remote sensing ecological index model was utilized to assess the ecological environment quality of the reserve. The single factor analysis and interactive detection analysis in geographical detector were applied to analyze the mechanisms of the seven influencing factors (NDVI, WET, LST, NDBSI, land use type, DEM, and population density) of RSEI. The results show that:(1) Compared with remote sensing ecological index model, the improved remote sensing ecological index model avoided the interference of feature vector direction, and could better reflect the changes of ecological environment quality. The ecological environment quality from 1986 to 2021 demonstrated a recovery trend of "first decreasing and then increasing", with a spatial distribution of "high in the east and low in the west". (2)The spatio-temporal differences in the reserve indicate that the ecological environment quality slightly deteriorated, unchanged or slightly improved in the past 35 years. The distribution of slightly deteriorated areas located mainly in the northern part of Sunan Yugur Autonomous County in Zhangye City and the junction of Zhangye City and Wuwei City. The slightly improved areas were scattered in the reserve, while the core areas were relatively more distributed in the reserve. (3) From the analysis of the causes of ecological environment quality, among the seven influencing factors, greenness (NDVI) had the strongest explanatory power on the spatial differentiation characteristics of RSEI. Considering the synergistic effect of multiple factors, the NDVI and NDBSI were the key driving indicators of ecological environment quality. The results above show that the ecological environment quality in Qilian Mountain Nature Reserve has been gradually improved in recent years, and a series of environment protection measures were effective.

Key words: improved remote sensing ecological index, Qilian Mountain National Nature Reserve, remote sensing dynamic monitoring, geographical detector, image availability analysis

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