Exploring Ecological Quality and Its Driving Factors in Diqing Prefecture, China, Based on Annual Remote Sensing Ecological Index and Multi-Source Data

The interaction between the natural environmental and socioeconomic factors is crucial for assessing the dynamics of plateau ecosystems. Therefore, the remote sensing ecological index (RSEI) and CatBoost-SHAP model were employed to investigate changes in the ecological quality and their driving factors in the Diqing Tibetan Autonomous Prefecture, China, from 2001 to 2021. The results showed an increase from 0.44 in 2001 to 0.71 in 2021 in the average RSEI for the Diqing Prefecture, indicating an overall upward trend in the ecological quality. Spatial analysis shows the percentage of the area covered by different levels of RSEI and their temporal changes. The results revealed that “good” ecological quality accounted for the largest proportion of the study area, at 42.77%, followed by “moderate” at 21.93%, and “excellent” at 16.62%. “Fair” quality areas accounted for 16.11% and “poor” quality areas only 2.57%. The study of ecological and socioeconomic drivers based on the CatBoost-SHAP framework also indicated that natural climate factors have a greater impact on ecological quality than socioeconomic factors; however, this effect differed significantly with altitude. The findings suggest that, in addition to strengthening climate monitoring, further advancements in ecological engineering are required to ensure the sustainable development of the ecosystem and the continuous improvement of the environmental quality in the Diqing Prefecture.

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Publication Details

Journal
Land
Published
2024-09-15
DOI
https://doi.org/10.3390/land13091499
Citations
5
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
1.41

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article

Exploring Ecological Quality and Its Driving Factors in Diqing Prefecture, China, Based on Annual Remote Sensing Ecological Index and Multi-Source Data

Qianqian Sheng, Chen Wang, Zunling Zhu
5 citations
Land
Land Use and Ecosystem Services
1.41
article

Exploring Ecological Quality and Its Driving Factors in Diqing Prefecture, China, Based on Annual Remote Sensing Ecological Index and Multi-Source Data

Qianqian Sheng, Chen Wang, Zunling Zhu
article en
5 citations

Abstract

The interaction between the natural environmental and socioeconomic factors is crucial for assessing the dynamics of plateau ecosystems. Therefore, the remote sensing ecological index (RSEI) and CatBoost-SHAP model were employed to investigate changes in the ecological quality and their driving factors in the Diqing Tibetan Autonomous Prefecture, China, from 2001 to 2021. The results showed an increase from 0.44 in 2001 to 0.71 in 2021 in the average RSEI for the Diqing Prefecture, indicating an overall upward trend in the ecological quality. Spatial analysis shows the percentage of the area covered by different levels of RSEI and their temporal changes. The results revealed that “good” ecological quality accounted for the largest proportion of the study area, at 42.77%, followed by “moderate” at 21.93%, and “excellent” at 16.62%. “Fair” quality areas accounted for 16.11% and “poor” quality areas only 2.57%. The study of ecological and socioeconomic drivers based on the CatBoost-SHAP framework also indicated that natural climate factors have a greater impact on ecological quality than socioeconomic factors; however, this effect differed significantly with altitude. The findings suggest that, in addition to strengthening climate monitoring, further advancements in ecological engineering are required to ensure the sustainable development of the ecosystem and the continuous improvement of the environmental quality in the Diqing Prefecture.

LandVol. 13(9)
Nanjing Forestry University (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 19%
Land Use and Ecosystem Services
1.41
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Exploring Ecological Quality and Its Driving Factors in Diqing Prefecture, China, Based on Annual Remote Sensing Ecological Index and Multi-Source Data — Qianqian Sheng, Chen Wang, et al. · Land (2024) | TGRS Research Map | TGRS