中文摘要：

Landsat-7机载扫描行校正器（Scan Line Corrector,SLC）失效后的ETM＋影像（SLC-OFF影像）约有22%的数据缺失,严重限制了该影像在冰川研究中的应用,特别对长期缺乏高质量遥感影像的高亚洲地区冰川运动连续监测产生较大影响.以Karakoram中部最大的锡亚琴冰川为例,初步评估了Landsat-7 ETM＋SLC-OFF影像在山地冰川表面流速提取方面的适用性和可行性.选取2009年和2010年两景SLC-OFF影像,运用局部直方图匹配法（Local Linear Histogram Match,LLHM）和加权线性回归法（Weighted Liner Regression,WLR）修复缺失数据条带,并利用亚像元互相关方法对修复后两景影像进行冰川表面流速估算.结果表明,LLHM和WLR两种方法均能有效修复冰川区Landsat-7 SLC-OFF影像,其冰流估算结果与同期Landsat-5 TM影像的冰流结果较为一致,三者冰流速估算精度分别为±5.9 m·a^-1、±6.3 m·a^-1和±4.0 m·a^-1,验证了Landsat-7 SLC-OFF影像在山地冰川流速监测中的应用潜力.

英文摘要：

When the Scan Line Corrector（SLC）on Landsat-7 loses efficacy and forms a wedge-shaped data gap in SLC-OFF image,resulting in roughly 22% of the pixel to be missed,and leaving a serious problem for the application of ETM ＋ data on studying glaciers,particularly for monitoring long- term glacial variations in High Asian Mountains,where there is fewhigh quality remote sensing data. In this study,the Siachen Glacier,the largest glacier in the Central Karakoram,was selected as a monitoring site. We aim to evaluate the potential of the Landsat-7 ETM＋ SLC-OFF images in deriving surface velocities of mountain glciers. A pair of SLC-OFF images acquired from 2009 and 2010 were used for this purpose. Two typical filling-gap methods,the localized linear histogram match（LLHM）and the weighted liner regression（WLR）,were utilized to recover the above mentioned SLC-OFF images. Then the recovered images were applied for deriving glacier surface flow velocities using sub-pixel correlation. The results show that both LLHM and WLR methods can effectively repair the glacier area in the Landsat-7 SLC-OFF images. Besides,the surface flow velocities estimated with the recovered SLC-OFF images are highly agreement with those from the Landsat-5 TM images. The accuracy of above three flow velocities are 5.9 m·a^-1,6.3 m·a^-1and 4.0 m·a^-1,respectively. This study verifies the potential of the Landsat-7 ETM＋ SLC-OFF images in deriving surface flow velocities of mountain glaciers.