Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies
Lakes in direct contact with glaciers (ice-marginal lakes) are found across alpine and polar landscapes. Many studies characterize ice-marginal lake behavior over multi-decadal timescales using either episodic ~annual images or multi-year mosaics. However, ice-marginal lakes are dynamic features tha...
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ftdoajarticles:oai:doaj.org/article:b28a40b403504505b2f7962c2c86f7af 2023-05-15T16:20:41+02:00 Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies Anton M. Hengst William Armstrong Brianna Rick Daniel McGrath 2021-10-01T00:00:00Z https://doi.org/10.3390/rs13193955 https://doaj.org/article/b28a40b403504505b2f7962c2c86f7af EN eng MDPI AG https://www.mdpi.com/2072-4292/13/19/3955 https://doaj.org/toc/2072-4292 doi:10.3390/rs13193955 2072-4292 https://doaj.org/article/b28a40b403504505b2f7962c2c86f7af Remote Sensing, Vol 13, Iss 3955, p 3955 (2021) Landsat Optical Remote Sensing Google Earth Engine land cover classification glacier cryosphere Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13193955 2022-12-31T09:43:38Z Lakes in direct contact with glaciers (ice-marginal lakes) are found across alpine and polar landscapes. Many studies characterize ice-marginal lake behavior over multi-decadal timescales using either episodic ~annual images or multi-year mosaics. However, ice-marginal lakes are dynamic features that experience short-term (i.e., day to year) variations in area and volume superimposed on longer-term trends. Through aliasing, this short-term variability could result in erroneous long-term estimates of lake change. We develop and implement an automated workflow in Google Earth Engine to quantify monthly behavior of ice-marginal lakes between 2013 and 2019 across south-central Alaska using Landsat 8 imagery. We employ a supervised Mahalanobis minimum-distance land cover classifier incorporating three datasets found to maximize classifier performance: shortwave infrared imagery, the normalized difference vegetation index (NDVI), and spatially filtered panchromatic reflectance. We observe physically-meaningful ice-marginal lake area variance on sub-annual timescales, with the median area fluctuation of an ice-marginal lake found to be 10.8% of its average area. The median signal (slow lake growth) to noise (physically-meaningful short-term area variability) ratio is 1.5:1, indicating that short-term variability is responsible for ~33% of observed area change in the median ice-marginal lake. The magnitude of short-term area variability is similar for ice-marginal and nonglacial lakes, suggesting that the cause of observed variations is not of glacial origin. These data provide a new context for interpreting behaviors observed in multi-decadal studies and encourage attention to sub-annual behavior of ice-marginal lakes even in long-term studies. Article in Journal/Newspaper glacier glaciers Alaska Directory of Open Access Journals: DOAJ Articles Marginal Lake ENVELOPE(163.500,163.500,-74.600,-74.600) Remote Sensing 13 19 3955 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Landsat Optical Remote Sensing Google Earth Engine land cover classification glacier cryosphere Science Q |
spellingShingle |
Landsat Optical Remote Sensing Google Earth Engine land cover classification glacier cryosphere Science Q Anton M. Hengst William Armstrong Brianna Rick Daniel McGrath Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
topic_facet |
Landsat Optical Remote Sensing Google Earth Engine land cover classification glacier cryosphere Science Q |
description |
Lakes in direct contact with glaciers (ice-marginal lakes) are found across alpine and polar landscapes. Many studies characterize ice-marginal lake behavior over multi-decadal timescales using either episodic ~annual images or multi-year mosaics. However, ice-marginal lakes are dynamic features that experience short-term (i.e., day to year) variations in area and volume superimposed on longer-term trends. Through aliasing, this short-term variability could result in erroneous long-term estimates of lake change. We develop and implement an automated workflow in Google Earth Engine to quantify monthly behavior of ice-marginal lakes between 2013 and 2019 across south-central Alaska using Landsat 8 imagery. We employ a supervised Mahalanobis minimum-distance land cover classifier incorporating three datasets found to maximize classifier performance: shortwave infrared imagery, the normalized difference vegetation index (NDVI), and spatially filtered panchromatic reflectance. We observe physically-meaningful ice-marginal lake area variance on sub-annual timescales, with the median area fluctuation of an ice-marginal lake found to be 10.8% of its average area. The median signal (slow lake growth) to noise (physically-meaningful short-term area variability) ratio is 1.5:1, indicating that short-term variability is responsible for ~33% of observed area change in the median ice-marginal lake. The magnitude of short-term area variability is similar for ice-marginal and nonglacial lakes, suggesting that the cause of observed variations is not of glacial origin. These data provide a new context for interpreting behaviors observed in multi-decadal studies and encourage attention to sub-annual behavior of ice-marginal lakes even in long-term studies. |
format |
Article in Journal/Newspaper |
author |
Anton M. Hengst William Armstrong Brianna Rick Daniel McGrath |
author_facet |
Anton M. Hengst William Armstrong Brianna Rick Daniel McGrath |
author_sort |
Anton M. Hengst |
title |
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
title_short |
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
title_full |
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
title_fullStr |
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
title_full_unstemmed |
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies |
title_sort |
short-term variability in alaska ice-marginal lake area: implications for long-term studies |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13193955 https://doaj.org/article/b28a40b403504505b2f7962c2c86f7af |
long_lat |
ENVELOPE(163.500,163.500,-74.600,-74.600) |
geographic |
Marginal Lake |
geographic_facet |
Marginal Lake |
genre |
glacier glaciers Alaska |
genre_facet |
glacier glaciers Alaska |
op_source |
Remote Sensing, Vol 13, Iss 3955, p 3955 (2021) |
op_relation |
https://www.mdpi.com/2072-4292/13/19/3955 https://doaj.org/toc/2072-4292 doi:10.3390/rs13193955 2072-4292 https://doaj.org/article/b28a40b403504505b2f7962c2c86f7af |
op_doi |
https://doi.org/10.3390/rs13193955 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
19 |
container_start_page |
3955 |
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1766008656021684224 |