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Dual scale trend analysis for evaluating climatic and anthropogenic effects on the vegetated land surface in Russia and Kazakhstan

机译:用于评估俄罗斯和哈萨克斯坦植被对气候和人为影响的双重尺度趋势分析

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We present a dual scale trend analysis for characterizing and comparing two contrasting areas of change in Russia and Kazakhstan that lie less than 800?km apart. We selected a global NASA MODIS (moderate resolution imaging spectroradiometer) product (MCD43C4 and MCD43A4) at a 0.05° (~5.6?km) and 500?m spatial resolution and a 16-day temporal resolution from 2000 to 2008. We applied a refinement of the seasonal Kendall trend method to the normalized difference vegetation index (NDVI) image series at both scales. We only incorporated composites during the vegetative growing season which was delineated by start of season and end of season estimates based on analysis of normalized difference infrared index data. Trend patterns on two scales pointed to drought as the proximal cause of significant declines in NDVI in Kazakhstan. In contrast, the area of increasing NDVI trend in Russia was linked through the dual scale analysis with agricultural land cover change. The coarser scale analysis was relevant to atmospheric boundary layer processes, while the finer scale data revealed trends that were more relevant to human decision-making and regional economics.
机译:我们提供了一个双尺度趋势分析,用于表征和比较俄罗斯和哈萨克斯坦相距不到800公里的两个相对变化区域。我们选择了全球NASA MODIS(中分辨率成像光谱仪)产品(MCD43C4和MCD43A4),从2000年到2008年,它们的空间分辨率为0.05°(〜5.6?km)和500?m,时间分辨率为16天。 Kendall趋势方法对两种尺度下的归一化植被指数(NDVI)图像序列的影响。我们仅在营养生长季节掺入了复合材料,根据标准化差异红外指数数据的分析,通过季节开始和季节结束来描述复合材料。两种尺度的趋势模式都表明干旱是哈萨克斯坦NDVI大幅下降的近因。相反,通过双重尺度分析将俄罗斯NDVI趋势增加的区域与农业土地覆盖变化联系在一起。较粗的尺度分析与大气边界层过程有关,而较细的尺度数据揭示了与人类决策和区域经济学更相关的趋势。

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