An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions
We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes ac...
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ftmdpi:oai:mdpi.com:/2072-4292/8/1/16/ 2023-08-20T04:05:02+02:00 An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions David Selkowitz Richard Forster agris 2015-12-25 application/pdf https://doi.org/10.3390/rs8010016 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs8010016 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 8; Issue 1; Pages: 16 remote sensing of glaciers snow and ice Landsat arctic Text 2015 ftmdpi https://doi.org/10.3390/rs8010016 2023-07-31T20:49:08Z We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly identify areas where substantial changes in glacier area have ... Text Arctic MDPI Open Access Publishing Arctic Remote Sensing 8 1 16 |
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Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
remote sensing of glaciers snow and ice Landsat arctic |
spellingShingle |
remote sensing of glaciers snow and ice Landsat arctic David Selkowitz Richard Forster An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
topic_facet |
remote sensing of glaciers snow and ice Landsat arctic |
description |
We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly identify areas where substantial changes in glacier area have ... |
format |
Text |
author |
David Selkowitz Richard Forster |
author_facet |
David Selkowitz Richard Forster |
author_sort |
David Selkowitz |
title |
An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
title_short |
An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
title_full |
An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
title_fullStr |
An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
title_full_unstemmed |
An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions |
title_sort |
automated approach for mapping persistent ice and snow cover over high latitude regions |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2015 |
url |
https://doi.org/10.3390/rs8010016 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Remote Sensing; Volume 8; Issue 1; Pages: 16 |
op_relation |
https://dx.doi.org/10.3390/rs8010016 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs8010016 |
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Remote Sensing |
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8 |
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