利用卫星衍生的高光谱指数识别植被

Archana Nandibewoor, R. Hegadi, Prashant Adiver
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引用次数: 3

摘要

高光谱遥感技术是研究植被速率的新兴技术之一。我们的研究采用了印第安纳州西部的高光谱卫星图像。这些数据进一步用于计算不同的光谱指数。本文介绍了随植被变化而发生显著变化的光谱指数的研究。这些光谱指数用于监测植被。使用的光谱指数有NDVI(归一化植被指数)、SRPI(简单比色素指数)、红边(Clrededge)和SG (VI绿)。以上光谱指标均随叶绿素速率和氮浓度的变化而发生显著变化。在不同波长与反射率值绘制的曲线图中,显示了不同的面积变化曲线。从本研究可以推断,高光谱数据还可以用于寻找含有茂密森林,农田和裸地的区域。因此,卫星图像可以提供许多需要探索的信息。
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Identification of vegetation from satellite derived hyper spectral indices
One of the emerging technologies that can be used to study the rate of vegetation is hyper spectral remote sensing. Hyper spectral satellite image of Western part of Indiana is adopted for our study. This data was further used to calculate different spectral indices. The study on spectral indices which show some significant changes with variation in Vegetation are presented in this paper. These spectral indices are used to monitor the vegetation. The spectral indices that are used are NDVI (normalized differential Vegetation index), SRPI (simple Ratio pigment index), red edge (Clrededge) and SG (VI green). All these spectral indices stated above showed significant changes with change in rate of chlorophyll and nitrogen Concentration. In the graph plotted for different wavelengths verses the reflectance values showed different Curves for change in the area. From this study it can be inferred that the hyper spectral data can also be used to find area containing dense forest, farm lands and bare land. Hence Satellite images can give lot of information that needs to be explored.
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