利用RADARSAT-2高分辨率图像评估无监督分类在冰足制图中的潜力

Simon Tolzczuk-Leclerc, E. Hudier, S. Bélanger
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引用次数: 0

摘要

随着新一代高分辨率极化SAR卫星的出现,提取像形成冰脚的海冰带一样狭窄的冰结构变得可能可行。2011年2月15日获得了一个RADARSAT-2场景,并测试了三个处理链来完成这项任务。研究发现,Lee和Pottier[2,4]方法,更具体地说,类分布中嵌入的信息提供了巨大的潜力。虽然某些环境(如海水或城市)可以使用单一类别进行分类,但在冰足和泥炭沼泽地区,后向散射过程涉及的机制范围更广,使得类别分布成为自动提取冰足的更好指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the potential of unsupervised classifications for icefoot cartograpy using RADARSAT-2 high resolution imagery
With the advent of a new generation of high resolution polarimetric SAR satellites, the extraction of ice structures as narrow as the strip of sea ice that forms the icefoot becomes potentially feasible. One RADARSAT-2 scene was acquired on February 15, 2011 and three processing chains were tested to accomplish this task. It was found that the Lee and Pottier [2, 4] method and more specifically the information imbedded in the class distribution offers a great potential. While some environments such as sea water or a city may be sorted out using a single class, the more diverse range of mechanisms involved into the backscattering processes in icefoot and peat bog areas make the class distribution a better indicator to automatically extract the icefoot.
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