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Estimating vegetation cover from high-resolution satellite data to assess grassland degradation in the Georgian Caucasus

机译:从高分辨率卫星数据估算植被覆盖率,以评估格鲁吉亚高加索地区的草地退化

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摘要

In the Georgian Caucasus, unregulated grazing has damaged grassland vegetation cover and caused erosion. Methods for monitoring and control of affected territories are urgently needed. Focusing on the high-montane and subalpine grasslands of the upper Aragvi Valley, we sampled grassland for soil, rock, and vegetation cover to test the applicability of a site-specific remote-sensing approach to observing grassland degradation. We used random-forest regression to separately estimate vegetation cover from 2 vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Modified Soil Adjusted Vegetation Index (MSAVI2), derived from multispectral WorldView-2 data (1.8 m). The good model fit of R2 = 0.79 indicates the great potential of a remote-sensing approach for the observation of grassland cover. We used the modeled relationship to produce a vegetation cover map, which showed large areas of grassland degradation.
机译:在格鲁吉亚的高加索地区,无节制的放牧破坏了草原植被的覆盖并造成了侵蚀。迫切需要监视和控制受影响地区的方法。着眼于阿拉格维河谷上游的高山和亚高山草原,我们对草原的土壤,岩石和植被进行了采样,以测试特定地点的遥感方法在观察草原退化方面的适用性。我们使用随机森林回归从两个植被指数(归一化差异植被指数(NDVI)和改良土壤调整植被指数(MSAVI2))中分别估算出植被覆盖度,该指数来自多光谱WorldView-2数据(1.8 m)。 R2 = 0.79的良好模型拟合表明,遥感方法可用于观测草地覆盖率。我们使用模型关系生成了植被覆盖图,该图显示了大面积的草地退化。

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