Combining polarimetric sentinel-1 and ALOS-2/PALSAR-2 imagery for mapping of flooded vegetation

S. Plank, Martin Jussi, S. Martinis, A. Twele
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引用次数: 2

Abstract

This article presents a semi-automated methodology for mapping of flooded areas with a special focus on flooded vegetation based on polarimetric Synthetic Aperture Radar (SAR) data. C-band SAR data is well suited for mapping of open water areas, while L-band enables the extraction of detailed information of flooded vegetation. Here, dual-pol C-band data of Sentinel-1 (S-1) is combined with quad-pol L-band ALOS-2/PALSAR-2 data to enable an accurate mapping of the entire flooded area. The developed procedure combines polarimetric decomposition based unsupervised Wishart classification with object-based post-classification refinement as well as the integration of spatial contextual information and global auxiliary data. The methodology was tested at the Evros River (Greek/Turkish border region), where a flooding event occurred in spring 2015.
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结合极化sentinel-1和ALOS-2/PALSAR-2影像进行淹没植被制图
本文提出了一种基于偏振合成孔径雷达(SAR)数据的半自动化洪水地区制图方法,并特别关注洪水植被。c波段SAR数据非常适合于开阔水域的制图,而l波段则可以提取淹没植被的详细信息。在这里,Sentinel-1 (S-1)的双pol c波段数据与四pol l波段ALOS-2/PALSAR-2数据相结合,可以精确绘制整个淹没区域。该方法将基于极化分解的无监督Wishart分类与基于对象的分类后细化相结合,并集成了空间上下文信息和全局辅助数据。该方法在埃夫罗斯河(希腊/土耳其边境地区)进行了测试,该地区在2015年春季发生了洪水事件。
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