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Quantitative contribution of climate change and human activities to vegetation cover variations based on GA-SVM model

机译:气候变化与人类活动对植被覆盖基于GA-SVM模型的变化的定量贡献

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摘要

Vegetation cover is a frequently used indicator for assessing terrestrial ecosystem conditions. It is important to investigate the spatial and temporal change patterns of vegetation cover, and quantify the effects of climate change and human activities on vegetation cover dynamics. In this study, the cross wavelet analysis was first applied to reveal the detailed associations between the Normalized Difference Vegetation Index (NDVI) and precipitation/air temperature, as well as their evolution characteristics. Then, a Support Vector Machine (SVM)based simulation model was introduced to quantify the effects of climate change and human activities on vegetation cover dynamics. Results indicated that: (1) the proposed GA-SVM model is reliable in reproducing the observed NDVI series; (2) the increasing trend of annual NDVI was primarily contributed by the increase in spring and autumn, during which precipitation and air temperature changes lead to the lengthening of vegetation growing season; (3) for the Wei River Basin as a whole, climate change effects (about 59.3%) on NDVI are stronger than those by human activities (nearly 40.7%), whereas human activities including the large-scale "Grain for Green" Program are exerting the dominant influences in the Beiluo River Basin. The findings of this study are helpful for guiding the ecological restoration practices in the Loess Plateau under the backdrop of changing environment.
机译:植被覆盖是评估陆地生态系统条件的常用指标。重要的是要调查植被覆盖的空间和时间变化模式,量化气候变化和人类活动对植被覆盖动态的影响。在该研究中,首先应用交叉小波分析以揭示归一化差异植被指数(NDVI)和沉淀/空气温度之间的详细关联,以及它们的进化特性。然后,引入了基于支持向量机(SVM)的仿真模型,以量化气候变化和人类活动对植被覆盖动态的影响。结果表明:(1)所提出的GA-SVM模型在再现观察到的NDVI系列方面是可靠的; (2)年度NDVI的趋势越来越大,春季和秋季的增加主要是贡献,在此期间降水和空气温度变化导致植被生长季节的延长; (3)对于魏河流域整体而言,气候变化效应(约59.3%)对NDVI的影响力强于人类活动(近40.7%),而在包括大规模“绿色粮食”计划中的人类活动是施加贝洛河流域的主导影响。本研究的调查结果有助于指导在不断变化环境的背景下黄土高原的生态恢复实践。

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