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Remotely Sensed Method for Detection of Spatial Distribution Pattern of Dryland Plants in Water Limited Ecosystem

机译:用于检测水有限生态系统中旱地植物空间分布图案的远程感测方法

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The Gobi Desert in Mongolia is characterized by sparse and patchy vegetation, interspersed with essentially bare areas. The vegetation pattern is typically formed by perennial shrubs, grasses or annually-herbaceous plant overlying a matrix composed of bare soil. Vegetation patterns, most broadly, refer to the spatial organization of vegetation in a landscape. However, since the plants in the Gobi Desert are sparsely distributed over a vast bare field, it is extremely difficult to accurately observe from satellite imagery. This is because reflectance of dry soil is very high and the reflectance of slightly distributed plants is eliminated by soil reflection. This study solves this problem by using field surveys and methods for combining different satellite sensor data and spectral un-mixing analysis. As a result, the pixel NDVI value of desert plants shows a smaller value than the ground measurement. It is shown that the fraction of the vegetation endmember after pixel un-mixing has a remarkably high correlation with the field measured values (where, R2=0.51 between NDVI of Landsat 8 imagery original pixels and un-mixed pixels and R2=0.79 between plants coverage of field measurement and un-mixed pixels percentage of vegetation endmembers).
机译:蒙古的戈壁沙漠的特点是稀疏和厚重的植被,散布着基本上裸露的地区。植被模式通常由多年生灌木,草或未覆盖由裸土壤组成的基质的植物形成。植被模式最广泛地指的是植被的空间组织在景观中。然而,由于戈壁沙漠中的植物稀疏地分布在庞大的裸露领域,因此极难从卫星图像准确地观察。这是因为干燥土壤的反射率非常高,并且通过土壤反射消除了略微分布的植物的反射率。本研究通过使用用于组合不同的卫星传感器数据和光谱不混合分析的现场调查和方法来解决这个问题。结果,沙漠植物的像素NDVI值显示比地面测量的较小值。结果表明,像素未混合之后的植被端部的部分与场测量值具有显着高的相关性(Landsat 8图像的NDVI之间的R2 = 0.51,原始像素和未混合像素之间的R2 = 0.79覆盖田间测量和未混合像素植被终点的百分比)。

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