ORIGINAL RESEARCH
Landscape Ecological Risk Assessment
and Evaluation of Influencing Factors of
Jinsha River Basin in Yunnan Province
Based on Land Use/Cover Change
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1
School of Information Science and Technology, Yunnan Normal University, Kunming, Yunnan, China, 650500
2
Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan Kunming, Yunnan, China,
650500
3
Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming, Yunnan, China, 650500
4
Faculty of Geography, Yunnan Normal University, Kunming, Yunnan, China, 650500
Submission date: 2024-06-20
Final revision date: 2024-08-14
Acceptance date: 2024-08-23
Online publication date: 2024-10-11
Corresponding author
Xue Ding
Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan Kunming, Yunnan, China,
650500
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ABSTRACT
The ecological quality of the Jinsha River Basin in Yunnan Province has been declining due to
human activities and global climate change. Thus, conducting a comprehensive landscape ecological
risk assessment is essential for reconciling ecological protection with economic development and
fostering sustainable regional growth. This study analyzes land-use and cover change data to evaluate
the landscape ecological risk in the Jinsha River Basin from 1985 to 2020. By calculating landscape
pattern indices and utilizing GIS technology to create a landscape risk index model, we further
investigate the spatiotemporal evolution patterns and influencing factors of ecological risk in the area.
The results reveal that: (1) Between 1985 and 2020, the primary landscape types in the Jinsha River
Basin were cultivated land, forest land, and grassland, collectively accounting for approximately 98%
of the total area. Notably, built-up land has increased continuously while grassland has decreased. (2)
The assessment indicates that the region predominantly experiences moderate, relatively high, and high
ecological risks, comprising over 80% of the area, with moderate and relatively high risks being the
most significant. High ecological risk areas are primarily concentrated in Kunming City and Qujing
City. (3) The global Moran's I value consistently exceeds 0.2 and exhibits a downward trend, indicating
a distribution of landscape ecological risk that is "high in the center, low at the edges," with local spatial
autocorrelation characterized by "high-high" (H-H) and "low-low" (L-L) clusters. (4) Controlling for
annual average precipitation reveals a positive correlation between annual average temperature and
ecological risk while controlling for temperature shows a negative correlation between annual average shortprecipitation
and ecological risk. The findings of this study provide valuable insights for optimizing
land resources and promoting sustainable development in the Jinsha River Basin.