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

Tabea Rettelbach,Johann-Christoph Freytag,Moritz Langer,Ingmar Nitze,Veit Helm,Guido Grosse,Benjamin Jones

doi:10.3390/rs13163098

Abstract

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.

Highlights

The presence of ground ice in the form of ice wedges is a major characteristic of permafrost soils [7]
In order to model and to monitor the process of landscape-scale polygonal ice-wedge degradation with quantifiable metrics, we propose a method to extract information from digital terrain models (DTM) on the depth, width, and length of ice-wedge troughs and further model their geomorphometric properties and spatial relationships as a graph, a concept from discrete mathematics used to represent complex networks [37]
With our approach at representing ice-wedge polygonal landscapes affected by permafrost thaw as graphs that we extracted from airborne Light Detection and Ranging (LiDAR) DTMs, we offer geomorphological and hydrological insights at unprecedented detail for changing Arctic tundra regions

Summary

Introduction

Covering approximately 15% of the northern hemisphere’s landmass, permafrost is a ubiquitous phenomenon in the terrestrial Arctic [1]. It is defined as ground that stays at or below 0 °C for a minimum period of two years [2]. As Arctic temperatures are rapidly increasing [3], permafrost is undergoing warming [4], leading to extensive permafrost thaw throughout the Arctic [5,6]. The presence of ground ice in the form of ice wedges is a major characteristic of permafrost soils [7]. Ice wedges form through soil contraction, frost cracking, and ice Remote Sens.

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