Spatial-Temporal Evolution of Vegetation NDVI in Association with Climatic, Environmental and Anthropogenic Factors in the Loess Plateau, China during 2000-2015: Quantitative Analysis Based on Geographical Detector Model

被引:36
|
作者
Dong, Yi [1 ]
Yin, Dongqin [1 ,2 ,3 ]
Li, Xiang [4 ,5 ,6 ]
Huang, Jianxi [1 ,2 ]
Su, Wei [1 ,2 ]
Li, Xuecao [1 ,2 ]
Wang, Hongshuo [1 ,2 ]
机构
[1] China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China
[2] Minist Agr & Rural Affairs, Key Lab Remote Sensing Agrihazards, Beijing 100083, Peoples R China
[3] Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing 100083, Peoples R China
[4] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cyde River, Beijing 100038, Peoples R China
[5] Minist Water Resources, Key Lab Sediment Sci & Northern River Regulat, Beijing 100038, Peoples R China
[6] Qinghai Univ, State Key Lab Plateau Ecol & Agr, Xining 810016, Peoples R China
基金
中国国家自然科学基金;
关键词
Loess Plateau; China; normalized difference vegetation index (NDVI); spatial-temporal evolution; geographical detector model; driving forces; SOIL-EROSION; TEMPERATURE; GROWTH; DYNAMICS; IMPACTS; DROUGHT; SURFACE; TRENDS; REGION; COVER;
D O I
10.3390/rs13214380
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the Loess Plateau (LP) of China, the vegetation degradation and soil erosion problems have been shown to be curbed after the implementation of the Grain for Green program. In this study, the LP is divided into the northwestern semi-arid area and the southeastern semi-humid area using the 400 mm isohyet. The spatial-temporal evolution of the vegetation NDVI during 2000-2015 are analyzed, and the driving forces (including factors of climate, environment, and human activities) of the evolution are quantitatively identified using the geographical detector model (GDM). The results showed that the annual mean NDVI in the entire LP was 0.529, and it decreased from the semi-humid area (0.619) to the semi-arid area (0.346). The mean value of the coefficient of variation of the NDVI was 0.1406, and it increased from the semi-humid area (0.1165) to the semi-arid area (0.1926). The annual NDVI growth rate in the entire LP was 0.0079, with the NDVI growing faster in the semi-humid area (0.0093) than in the semi-arid area (0.0049). The largest increments of the NDVI were from grassland, farmland, and woodland. The GDM results revealed that changes in the spatial distribution of the NDVI could be primarily explained by the climatic and environmental factors in the semi-arid area, such as precipitation, soil type, and vegetation type, while the changes were mainly explained by the anthropogenic factors in the semi-humid area, such as the GDP density, land-use type, and population density. The interactive analysis showed that interactions between factors strengthened the impacts on the vegetation change compared with an individual factor. Furthermore, the ranges/types of factors suitable for vegetation growth were determined. The conclusions of this study have important implications for the formulation and implementation of ecological conservation and restoration strategies in different regions of the LP.</p>
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页数:30
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    Li, Xing
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