期刊
REMOTE SENSING OF ENVIRONMENT
卷 170, 期 -, 页码 372-387出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2015.10.001
关键词
Debris-covered glacier; Object-based image analysis; Landsat 8; SAR coherence; Semi-automatic classification; Himalayas
资金
- ResClim
- Meltzer
- European Research Council under the European Union's Seventh Framework Programme (FP)/ERC [320816]
- ESA project Glaciers_cci [4000109873/14/I-NB]
- Austrian Science Fund (FWF) through the project iSLIDE [P 25446-N29]
- Austrian Science Fund (FWF) [P 25446] Funding Source: researchfish
Satellite imagery is increasingly used to monitor glacier area changes and create glacier inventories. Robust and efficient pixel-based band ratios have proven to be accurate for automatically delineating clean glacier ice, however such classifications are restricted on debris-covered ice due to its spectral similarity with surrounding terrain. Object-Based Image Analysis (OBIA) has emerged as a new analysis technique within remote sensing. It offers many advantages over pixel-based classification techniques due to the ability to work with multiple data sources and handle data contextually and hierarchically. By making use of OBIA capabilities we automatically classify dean ice and debris-covered ice in the challenging area surrounding Mount Manaslu in Nepal using optical (Landsat 8), topographic (void-filled SRTM) and SAR coherence (ALOS PALSAR) data. Clean ice was classified with a mean accuracy of 93% whilst debris-covered ice was classified with an accuracy of 83% when compared to manually corrected outlines, providing a total glacier accuracy of 91%. With further developments in the classification, steep tributary sections of ice could be contextually included, raising the accuracy to over 94%. One prominent advantage of OBIA is that it allows some post-processing and correction of the glacier outlines automatically, reducing the amount of manual correction needed. OBIA incorporating SAR coherence data is recommended for future mapping of debris-covered ice. (C) 2015 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据