Analysis of spatio-temporal dynamics and driving forces of vegetation cover in the Hutuo River Basin based on the geographic detector
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Graphical Abstract
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Abstract
The Hutuo River Basin, located in the Shanxi and Hebei Provinces, plays an important role in regional ecological environment and urban development. Analysis of the spatio-temporal dynamics and driving forces of vegetation cover in the area provides an important scientific basis for sustainable social and economic development and ecological environmental protection. Based on the monthly scale MOD13Q1 (250 m) dataset for 21 years from 2000 to 2020, this study analyzed the spatio-temporal variation trend of vegetation using the unary linear regression method and discussed the correlation between temperature, precipitation, and NDVI using the Pearson correlation analysis method. Natural factors such as temperature, precipitation, vegetation type, soil type, and altitude, and human factors such as land use type, population density, and GDP were statistically divided using the geographic detector, and the degree of influence of each driving factor on NDVI was systematically discussed. Particularly in the case of the increasingly close relationship between vegetation cover and human activities, the driving force values of different human factors can be obtained quantitatively to provide a basis for future research and analysis of the influence mechanism of the main driving factors, ecological environment protection, and sustainable development of watershed. The results of this study were as follows: 1) In the past 21 years, vegetation cover in the area had been increasing, and the average NDVI and Slope index, which is used to indicate vegetation changing trend with the positive value meaning increase, from May to September every year were 0.71 and 0.0035, respectively. The vegetation restoration in the area improved slightly, with 81.00% of the area improving in NDVI and 10.08% of the area degrading. 2) There were positive correlations between NDVI and precipitation and temperature in the area, and the interannual variation in NDVI was more closely related to precipitation. The proportions of positive and negative correlation areas between precipitation and NDVI were 87.73% and 12.27%, respectively, among which 35.28% and 6.92% of the positive correlation area passed the significance test of P<0.05 and P<0.01, respectively. However, the NDVI in the surrounding areas of Yangquan and Shijiazhuang cities was negatively correlated with precipitation and temperature, which may be significantly affected by human activities. 3) The degree of influence of a single driving factor on NDVI in the area was ranked from high to low as follows: precipitation > temperature > land use type > vegetation type > soil type > population density > GDP > altitude. Among them, the q (showing impacting strength of factor) values of the first three factors were all greater than 0.3, and they were the main driving factors affecting the NDVI in the area. 4) The driving force of all the driving factors combined in pairs was significantly greater than that of a single driving factor, showing a two-factor enhancement effect. In addition, the interaction between land use type and precipitation, with a q value of 0.74, was the largest, and it was significantly greater than that of interactions between only human factors or only natural factors. In general, human activities have had a strong impact on the spatio-temporal pattern of vegetation cover, and comprehensive consideration of meteorological factors and rational planning of land use are key factors in improving vegetation cover in the area.
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