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Use of satellite SAR for monitoring rain forest

机译:利用卫星SAR监测雨林

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Abstract: In this paper we compare the capability of Landsat TM optical imagery, JERS L-band and Radarsat C-band SAR for classifying rain forest into forest and not forest categories. In each case, simulated annealing provides the global optimum segmentation of the underlying variable. For the optical image the information is carried by the brightness, for JERS1 by the mean intensity and for Radarsat by the scene texture, where texture can be optimally measured in terms of the normalized log. We demonstrate that JERS1 and Radarsat provide similar classification into forest and not forest categories, when Landsat TM Band 5 imagery is adopted as the reference. Most of the discrepancies arise in regions of regeneration, where the physical difference between the imaging mechanisms of the three sensors has greatest impact.!21
机译:摘要:本文比较了Landsat TM光学图像,JERS L波段和Radarsat C波段SAR将雨林分类为森林而非森林的能力。在每种情况下,模拟退火均提供了基础变量的全局最佳分段。对于光学图像,信息由亮度承载,JERS1由平均强度承载,而Radarsat由场景纹理承载,其中可以根据归一化对数最佳地测量纹理。当采用Landsat TM Band 5影像作为参考时,我们证明JERS1和Radarsat提供了相似的森林分类,而不是森林分类。大多数差异出现在再生区域,在这三个传感器的成像机制之间的物理差异影响最大。21

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