Monitoring the Transformation of Arctic Landscapes: Automated Shoreline Change Detection of Lakes Using Very High Resolution Imagery


Contact
soraya.kaiser [ at ] awi.de

Abstract

Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40–0.56 myr^-1 for lake sizes of 0.10 ha–23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.



Item Type
Article
Authors
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Primary Division
Programs
Primary Topic
Helmholtz Cross Cutting Activity (2021-2027)
N/A
Peer revision
Peer-reviewed, Web of Science / Scopus
Publication Status
Published
Eprint ID
54434
DOI 10.3390/rs13142802

Cite as
Kaiser, S. , Grosse, G. , Boike, J. and Langer, M. (2021): Monitoring the Transformation of Arctic Landscapes: Automated Shoreline Change Detection of Lakes Using Very High Resolution Imagery , Remote Sensing, 13 (14), p. 2802 . doi: 10.3390/rs13142802


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Arctic Land Expeditions > AK-Land_2018_Deadhorse


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