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

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. A...

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Main Authors: T. Smith, B. Bookhagen, F. Cannon
Format: Article
Language:English
Published: Copernicus Publications 2015-09-01
Series:The Cryosphere
Online Access:http://www.the-cryosphere.net/9/1747/2015/tc-9-1747-2015.pdf
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spelling doaj-4688337e08d64dffb2796e5b2b4c02bb2020-11-24T22:27:52ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242015-09-01951747175910.5194/tc-9-1747-2015Improving semi-automated glacier mapping with a multi-method approach: applications in central AsiaT. Smith0B. Bookhagen1F. Cannon2Institute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, GermanyInstitute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, GermanyGeography Department, University of California, Santa Barbara, USAStudies 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. <br><br> 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. <br><br> 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.http://www.the-cryosphere.net/9/1747/2015/tc-9-1747-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author T. Smith
B. Bookhagen
F. Cannon
spellingShingle T. Smith
B. Bookhagen
F. Cannon
Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
The Cryosphere
author_facet T. Smith
B. Bookhagen
F. Cannon
author_sort T. Smith
title Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
title_short Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
title_full Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
title_fullStr Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
title_full_unstemmed Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
title_sort improving semi-automated glacier mapping with a multi-method approach: applications in central asia
publisher Copernicus Publications
series The Cryosphere
issn 1994-0416
1994-0424
publishDate 2015-09-01
description 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. <br><br> 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. <br><br> 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.
url http://www.the-cryosphere.net/9/1747/2015/tc-9-1747-2015.pdf
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