ABSTRACT. Deriving glacier outlines from satellite data has become increasingly popular in the past decade. In particular when glacier outlines are used as a base for change assessment, it is important to know how accurate they are. Calculating the accuracy correctly is challenging, as appropriate reference data (e.g. from higher-resolution sensors) are seldom available. Moreover, after the required manual correction of the raw outlines (e.g. for debris cover), such a comparison would only reveal the accuracy of the analyst rather than of the algorithm applied. Here we compare outlines for clean and debriscovered glaciers, as derived from single and multiple digitizing by different or the same analysts on very high-(1 m) and medium-resolution (30 m) remote-sensing data, against each other and to glacier outlines derived from automated classification of Landsat Thematic Mapper data. Results show a high variability in the interpretation of debris-covered glacier parts, largely independent of the spatial resolution (area differences were up to 30%), and an overall good agreement for clean ice with sufficient contrast to the surrounding terrain (differences $5%). The differences of the automatically derived outlines from a reference value are as small as the standard deviation of the manual digitizations from several analysts. Based on these results, we conclude that automated mapping of clean ice is preferable to manual digitization and recommend using the latter method only for required corrections of incorrectly mapped glacier parts (e.g. debris cover, shadow).
Abstract. Floods resulting from the outbursts of glacial lakes are among the most far-reaching disasters in high mountain regions. Glacial lakes are typically located in remote areas and space-borne remote sensing data are an important source of information about the occurrence and development of such lakes. Here we show that very high resolution satellite Synthetic Aperture Radar (SAR) data can be employed for reliably mapping glacial lakes. Results in the Alps, Pamir and Himalaya using TerraSAR-X and Radarsat-2 data are discussed in comparison to in-situ information, and highresolution satellite optical and radar imagery. The performance of the satellite SAR data is best during the snow-and ice-free season. In the broader perspective of hazard management, the detection of glacial lakes and the monitoring of their changes from very high-resolution satellite SAR intensity images contributes to the initial assessment of hazards related to glacial lakes, but a more integrated, multi-level approach needs also to include other relevant information such as glacier outlines and outline changes or the identification of unstable slopes above the lake and the surrounding area, information types to which SAR analysis techniques can also contribute.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.