Next Article in Journal
Estimation and Analysis of the Observable-Specific Code Biases Estimated Using Multi-GNSS Observations and Global Ionospheric Maps
Next Article in Special Issue
Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps
Previous Article in Journal
A Wheat Spike Detection Method in UAV Images Based on Improved YOLOv5
Previous Article in Special Issue
Monitoring the Transformation of Arctic Landscapes: Automated Shoreline Change Detection of Lakes Using Very High Resolution Imagery
 
 
Article

A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes

1
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, 14473 Potsdam, Germany
2
Institute of Geosciences, University of Potsdam, 14476 Potsdam, Germany
3
Department of Computer Science, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
4
Geography Department, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
5
Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
6
Glaciology Division, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, 27568 Bremerhaven, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Michael Lim
Remote Sens. 2021, 13(16), 3098; https://doi.org/10.3390/rs13163098
Received: 24 June 2021 / Revised: 28 July 2021 / Accepted: 31 July 2021 / Published: 5 August 2021
(This article belongs to the Special Issue Dynamic Disturbance Processes in Permafrost Regions)
In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-wedge polygons. This process has important implications for surface hydrology, as the connectivity of such troughs determines the rate of drainage for these lowland landscapes. In this study, we present a comprehensive, modular, and highly automated workflow to extract, to represent, and to analyze remotely sensed ice-wedge polygonal trough networks as a graph (i.e., network structure). With computer vision methods, we efficiently extract the trough locations as well as their geomorphometric information on trough depth and width from high-resolution digital elevation models and link these data within the graph. Further, we present and discuss the benefits of graph analysis algorithms for characterizing the erosional development of such thaw-affected landscapes. Based on our graph analysis, we show how thaw subsidence has progressed between 2009 and 2019 following burning at the Anaktuvuk River fire scar in northern Alaska, USA. We observed a considerable increase in the number of discernible troughs within the study area, while simultaneously the number of disconnected networks decreased from 54 small networks in 2009 to only six considerably larger disconnected networks in 2019. On average, the width of the troughs has increased by 13.86%, while the average depth has slightly decreased by 10.31%. Overall, our new automated approach allows for monitoring ice-wedge dynamics in unprecedented spatial detail, while simultaneously reducing the data to quantifiable geometric measures and spatial relationships. View Full-Text
Keywords: patterned ground; ice wedges; degradation; computer vision; graph analysis; remote sensing; permafrost; image processing patterned ground; ice wedges; degradation; computer vision; graph analysis; remote sensing; permafrost; image processing
Show Figures

Graphical abstract

  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.5015072
    Link: https://github.com/trettelbach/IWD_graph_analysis/tree/v.1.0.0
    Description: A repository containing data and scripts for the publication by Rettelbach et al. "A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes" (in prep.).
MDPI and ACS Style

Rettelbach, T.; Langer, M.; Nitze, I.; Jones, B.; Helm, V.; Freytag, J.-C.; Grosse, G. A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes. Remote Sens. 2021, 13, 3098. https://doi.org/10.3390/rs13163098

AMA Style

Rettelbach T, Langer M, Nitze I, Jones B, Helm V, Freytag J-C, Grosse G. A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes. Remote Sensing. 2021; 13(16):3098. https://doi.org/10.3390/rs13163098

Chicago/Turabian Style

Rettelbach, Tabea, Moritz Langer, Ingmar Nitze, Benjamin Jones, Veit Helm, Johann-Christoph Freytag, and Guido Grosse. 2021. "A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes" Remote Sensing 13, no. 16: 3098. https://doi.org/10.3390/rs13163098

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop