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Chinese Journal of Ecology ›› 2023, Vol. 42 ›› Issue (10): 2545-2554.doi: 10.13292/j.1000-4890.202310.034

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Dynamic monitoring and evaluation of eco-environmental quality in the upper reaches of the Yellow River based on GEE: A case study of the section from Longyang Gorge to Jishi Gorge.

ZHOU Zhe1, HU Xiasong1, LIU Changyi1*, FU Jiangtao2, ZHAO Jimei3, XING Guangyan3, HE Weipeng1#br#

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  1. (1Department of Geological Engineering, Qinghai University, Xining 810016, China; 2Qinghai Academy of Agriculture and Forestry Sciences, Xining 810016, China; 3College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, China).

  • Online:2023-10-10 Published:2023-10-08

Abstract: This study aimed to clarify the temporal variations of eco-environmental quality of the section from Longyang Gorge to Jishi Gorge in the upper reaches of the Yellow River. Based on remote sensing big data platform of Google Earth Engine (GEE) and Landsat TM/OLI remote sensing images, we constructed a remote sensing ecological index (RSEI) model, evaluated the variations of eco-environmental quality of the section from Longyang Gorge to Jishi Gorge during 2000-2020, and analyzed influencing factors. The results showed that the eco-environmental quality was deteriorated first and then improved during 2000-2020. The eco-environmental quality in the region was slightly or moderately degraded during 2000-2010, while it was slightly or moderately improved during 2010-2020. The explanatory power of dryness, greenness, humidity, and heat followed a descending order during 2000-2020. The double-factor interaction between greenness and humidity had the strongest influence on eco-environmental quality during 2000-2010. Our results can provide theoretical support and practical guidance for eco-environment management, vegetation restoration, and ecological monitoring, as well as effective protection of the eco-environment in the upper reaches of the Yellow River.


Key words: remote sensing-based ecological index (RSEI), Google Earth Engine, principal component analysis, geographical detector.