Author
Listed:
- Xin Jia
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Haiyan Liu
(School of Economics and Management, China University of Geosciences, Beijing 100083, China)
- Xiaoyuan Zhang
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Lijiang Liang
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Dongya Liu
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Xinqi Zheng
(School of Information Engineering, China University of Geosciences, Beijing 100083, China
Observation and Research Station of Beijing Fangshan Comprehensive Exploration, Ministry of Natural Resources, Beijing 100083, China
Technology Innovation Center for Territory Spatial Big-Data, Ministry of Natural Resources of the People’s Republic of China, Beijing 100036, China)
Abstract
Vegetation dynamics and their underlying driving mechanisms have emerged as a prominent research focus in ecological studies of the Chinese Loess Plateau (CLP). Current investigations, however, employ simplified methodologies in analyzing the influencing factors, limiting their capacity to comprehensively elucidate the intricate and multidimensional mechanisms that govern vegetation transformations. Utilizing fractional vegetation cover (FVC) datasets spanning 2000 to 2021, this research applies both XGBoost-SHAP and Geodetector approaches for comparative analysis of the driving factors and precise quantification of climatic change (CC) and human activity (HA). The results indicate that: (1) The CLP has experienced an annual FVC increase of 0.62%, with 95.1% of the region demonstrating statistically significant vegetation improvement. (2) Precipitation and land use emerge as the primary determinants of FVC spatial distribution, with their interactive effects substantially exceeding the impacts of individual factors. (3) While both XGBoost-SHAP and Geodetector methodologies consistently identify the primary driving factors, notable discrepancies exist in their assessment of temperature’s relative importance, revealing complementary dimensions of ecological complexity captured by different analytical paradigms. (4) Approximately 94.3% of FVC variations are jointly influenced by HA and CC, with anthropogenic factors predominating at a contribution of 67%. Land use modifications, particularly transitions among cropland, grassland, and forests, constitute the principal mechanism of human influence on vegetation patterns. This investigation enhances the understanding of vegetation responses under combined natural and anthropogenic pressures, offering valuable insights for ecological rehabilitation and sustainable development strategies on the CLP.
Suggested Citation
Xin Jia & Haiyan Liu & Xiaoyuan Zhang & Lijiang Liang & Dongya Liu & Xinqi Zheng, 2025.
"Exploring the Spatiotemporal Driving Forces of Vegetation Cover Variations on the Loess Plateau: A Comprehensive Assessment of Climate Change and Human Activity,"
Land, MDPI, vol. 14(5), pages 1-21, April.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:5:p:929-:d:1641829
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