New Vegetation Indices For Full And Compact Polarimetric Sar Data: In Preparation For The Radarsat Constellation Mission (RCM)

D. Ratha, D. Mandal, S. Dey, A. Bhattacharya, A. Frery, Y. S. Rao, H. Mcnairn
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引用次数: 2

Abstract

In this paper, we present two radar vegetation indices for full-pol and compact-pol SAR data, respectively. Both are derived using the notion of a geodesic distance between observation and well-known scattering models available in the literature. While the full-pol version depends on a generalized volume scattering model, the compact-pol version uses the ideal depolariser to model the randomness in the vegetation. We have utilized the RADARSAT Constellation Mission (RCM) time-series data from the SAMPVEX16-MB campaign in the Manitoba region of Canada for comparing and assessing the indices in terms of the change in the biophysical parameters as well. The compact-pol data for comparison is simulated from the full-pol RCM time series. Both the indices show better performance at correlating with biophysical parameters such as Plant Area Index (PAI) and Volumetric Water Content (VWC) for wheat and soybean crops, in comparison to the state-of-art Radar Vegetation Index (RVI) of Kim and van Zyl. These indices are timely for the upcoming release of the data from the RCM, which will provide data in both full and compact-pol modes, aimed at better crop monitoring from space.
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面向全和紧凑极化Sar数据的新植被指数:为雷达卫星星座任务(RCM)做准备
本文分别给出了全pol和小pol SAR数据的两种雷达植被指数。两者都是利用观测和文献中已知的散射模型之间的测地线距离的概念推导出来的。而全pol版本依赖于一个广义的体积散射模型,紧凑pol版本使用理想去极化器来模拟植被的随机性。我们还利用加拿大马尼托巴地区SAMPVEX16-MB活动的RADARSAT星座任务(RCM)时间序列数据来比较和评估生物物理参数变化方面的指标。用全pol RCM时间序列模拟了紧凑pol数据进行比较。与Kim和van Zyl的最新雷达植被指数(RVI)相比,这两种指数在与小麦和大豆作物的植物面积指数(PAI)和体积含水量(VWC)等生物物理参数的相关性方面表现更好。这些指数对于即将发布的RCM数据来说是及时的,RCM将提供完整和紧凑模式的数据,旨在更好地从空间监测作物。
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