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Improving Semi-automated Glacier Mapping with a Multi-method Approach: Applications in Central Asia : Volume 9, Issue 5 (04/09/2015)

By Smith, T.

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Book Id: WPLBN0004023480
Format Type: PDF Article :
File Size: Pages 13
Reproduction Date: 2015

Title: Improving Semi-automated Glacier Mapping with a Multi-method Approach: Applications in Central Asia : Volume 9, Issue 5 (04/09/2015)  
Author: Smith, T.
Volume: Vol. 9, Issue 5
Language: English
Subject: Science, Cryosphere
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Cannon, F., Bookhagen, B., & Smith, T. (2015). Improving Semi-automated Glacier Mapping with a Multi-method Approach: Applications in Central Asia : Volume 9, Issue 5 (04/09/2015). Retrieved from http://www.worldlibrary.in/


Description
Description: Institute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, Germany. Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity.

In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10 % of glacier areas, as compared to a ~ 750 glacier control data set, and can reliably classify a given Landsat scene in 3–5 min.

The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.


Summary
Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia

Excerpt
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