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ENVISAT-ASAR Data Analysis for Snow Cover Mapping over Gangotri Region

机译:甘蔗群地区雪覆盖映射的Envisat-Asar数据分析

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Snow cover area (SCA) mapping is very important parameter for snowmelt runoff modeling and forecasting. Snow cover information is also useful for managing transportation and avalanche forecasting. For SCA mapping, we selected Gangotri area and ENVISAT ASAR swath-2 data sets acquired during 2003-2004. The ASAR SLC data are converted into backscattering coefficient. The backscattering coefficient images are co-registered, multi-looked and geocoded using freely available DORIS InSAR software package. Out of available images during 2 years, Nov. 2003 image was taken as a reference image to form a ratio image with respect to others. Snow covered and non-snow areas are classified using threshold value (less than -3 dB is considered as snow) based on change detection method as given by Nagler and Rott. This value is shifted to -2dB to match with the classified snow cover area from optical data of IRS-ID. With five pairs of ratio images we could observe seasonal change of snow. The problem with the technique is that it can not be used with different ASAR mode data. The threshold value also depends on the location of the area.
机译:雪覆盖区(SCA)映射是雪花径流建模和预测的非常重要的参数。雪覆盖信息也可用于管理运输和雪崩预测。对于SCA映射,我们选择了2003-2004期间收购的甘塔利区域和Envisat ASAR Swath-2数据集。 ASAR SLC数据被转换为反向散射系数。反向散射系数图像使用自由可用的Doris Insar软件包共同登记,多眼睛和地理编码。在2年内退出可用图像,11月2003年图像被视为参考图像,以形成与他人的比率图像。基于名称和罗特给出的改变检测方法,使用阈值(小于-3 dB)分类雪覆盖和非雪地区域。此值移动到-2dB以与IRS-ID的光学数据与分类的雪覆盖区域匹配。使用五对比例的图像,我们可以观察雪的季节变化。该技术的问题是它不能与不同的ASAR模式数据一起使用。阈值也取决于该区域的位置。

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