The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images

The climate of the Arctic is warming rapidly and this is causing major changes to the cycling of carbon and the distribution of permafrost in this region. Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim...

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Published in:Remote Sensing
Main Authors: Ivan Sudakov, Almabrok Essa, Luke Mander, Ming Gong, Tharanga Kariyawasam
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2017
Subjects:
Q
Online Access:https://doi.org/10.3390/rs9101072
https://doaj.org/article/55003ced7ec84fe1ae010fe4f22a64fe
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spelling ftdoajarticles:oai:doaj.org/article:55003ced7ec84fe1ae010fe4f22a64fe 2023-05-15T14:54:28+02:00 The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images Ivan Sudakov Almabrok Essa Luke Mander Ming Gong Tharanga Kariyawasam 2017-10-01T00:00:00Z https://doi.org/10.3390/rs9101072 https://doaj.org/article/55003ced7ec84fe1ae010fe4f22a64fe EN eng MDPI AG https://www.mdpi.com/2072-4292/9/10/1072 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9101072 https://doaj.org/article/55003ced7ec84fe1ae010fe4f22a64fe Remote Sensing, Vol 9, Iss 10, p 1072 (2017) Arctic permafrost tundra lakes image processing fractals power law Science Q article 2017 ftdoajarticles https://doi.org/10.3390/rs9101072 2022-12-31T15:21:24Z The climate of the Arctic is warming rapidly and this is causing major changes to the cycling of carbon and the distribution of permafrost in this region. Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large (> 0.8 km 2 ) tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale 0.21166 km/pixel) and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale 0.1503 km/pixel). The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal dimension bifurcates. For lakes observed in historical maps, this bifurcation occurs among lakes larger than 100 km 2 (fractal dimension 1.43 to 1.87 ). For lakes observed in satellite images this bifurcation occurs among lakes larger than ∼100 km 2 (fractal dimension 1.31 to 1.95 ). Tundra lakes with a fractal dimension close to 2 have a tendency to be self-similar with respect to their area–perimeter relationships. Area–perimeter measurements indicate that lakes with a length scale greater than 70 km 2 are power-law distributed. Preliminary analysis of changes in lake size over time in paired lakes (lakes that were visually matched in both the historical map and the satellite imagery) indicate that some lakes in our study region have increased in size over time, whereas others have decreased in size over time. Lake size change during this 39-year time interval can be up to half the size of the lake as recorded in the historical map. Article in Journal/Newspaper Arctic permafrost Tundra Directory of Open Access Journals: DOAJ Articles Arctic Remote Sensing 9 10 1072
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic
permafrost
tundra lakes
image processing
fractals
power law
Science
Q
spellingShingle Arctic
permafrost
tundra lakes
image processing
fractals
power law
Science
Q
Ivan Sudakov
Almabrok Essa
Luke Mander
Ming Gong
Tharanga Kariyawasam
The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
topic_facet Arctic
permafrost
tundra lakes
image processing
fractals
power law
Science
Q
description The climate of the Arctic is warming rapidly and this is causing major changes to the cycling of carbon and the distribution of permafrost in this region. Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large (> 0.8 km 2 ) tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale 0.21166 km/pixel) and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale 0.1503 km/pixel). The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal dimension bifurcates. For lakes observed in historical maps, this bifurcation occurs among lakes larger than 100 km 2 (fractal dimension 1.43 to 1.87 ). For lakes observed in satellite images this bifurcation occurs among lakes larger than ∼100 km 2 (fractal dimension 1.31 to 1.95 ). Tundra lakes with a fractal dimension close to 2 have a tendency to be self-similar with respect to their area–perimeter relationships. Area–perimeter measurements indicate that lakes with a length scale greater than 70 km 2 are power-law distributed. Preliminary analysis of changes in lake size over time in paired lakes (lakes that were visually matched in both the historical map and the satellite imagery) indicate that some lakes in our study region have increased in size over time, whereas others have decreased in size over time. Lake size change during this 39-year time interval can be up to half the size of the lake as recorded in the historical map.
format Article in Journal/Newspaper
author Ivan Sudakov
Almabrok Essa
Luke Mander
Ming Gong
Tharanga Kariyawasam
author_facet Ivan Sudakov
Almabrok Essa
Luke Mander
Ming Gong
Tharanga Kariyawasam
author_sort Ivan Sudakov
title The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
title_short The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
title_full The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
title_fullStr The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
title_full_unstemmed The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite Images
title_sort geometry of large tundra lakes observed in historical maps and satellite images
publisher MDPI AG
publishDate 2017
url https://doi.org/10.3390/rs9101072
https://doaj.org/article/55003ced7ec84fe1ae010fe4f22a64fe
geographic Arctic
geographic_facet Arctic
genre Arctic
permafrost
Tundra
genre_facet Arctic
permafrost
Tundra
op_source Remote Sensing, Vol 9, Iss 10, p 1072 (2017)
op_relation https://www.mdpi.com/2072-4292/9/10/1072
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs9101072
https://doaj.org/article/55003ced7ec84fe1ae010fe4f22a64fe
op_doi https://doi.org/10.3390/rs9101072
container_title Remote Sensing
container_volume 9
container_issue 10
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