An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery

Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap i...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 13; no. 4; p. 558
Main Authors: Witharana, Chandi, Bhuiyan, Md Abul Ehsan, Liljedahl, Anna K., Kanevskiy, Mikhail, Jorgenson, Torre, Jones, Benjamin M., Daanen, Ronald, Epstein, Howard E., Griffin, Claire G., Kent, Kelcy, Ward Jones, Melissa K.
Format: Journal Article
Language:English
Published: Basel MDPI AG 04.02.2021
Subjects:
Accuracy
Adaptation
Algorithms
Arctic
Arctic region
Arctic zone
Assessments
Carbon
Classification
Climate system
Coastal plains
Cold
commercial imagery
Completeness
Global climate
Hydrology
Ice environments
ice-wedge polygons
Image analysis
Image classification
Image enhancement
Image processing
Image quality
Image segmentation
Interoperability
landscapes
Mapping
Mathematical models
OBIA
Permafrost
Polygons
Regions
Remote sensing
riparian areas
Satellite imagery
Satellite observation
Satellites
Spatial discrimination
Spatial resolution
Taiga & tundra
Topography
troughs
Tundra
Vegetation
Workflow
Arctic region
ISSN:2072-4292, 2072-4292
Online Access:Get full text
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Summary:Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap in spatial resolution and geographical coverage. This likely introduced biases in climate impacts on, and feedback from the Arctic region to the global climate system. The central objective of this exploratory study is to develop an object-based image analysis workflow to automatically extract ice-wedge polygon troughs from very high spatial resolution commercial satellite imagery. We employed a systematic experiment to understand the degree of interoperability of knowledge-based workflows across distinct tundra vegetation units—sedge tundra and tussock tundra—focusing on the same semantic class. In our multi-scale trough modelling workflow, we coupled mathematical morphological filtering with a segmentation process to enhance the quality of image object candidates and classification accuracies. Employment of the master ruleset on sedge tundra reported classification accuracies of correctness of 0.99, completeness of 0.87, and F1 score of 0.92. When the master ruleset was applied to tussock tundra without any adaptations, classification accuracies remained promising while reporting correctness of 0.87, completeness of 0.77, and an F1 score of 0.81. Overall, results suggest that the object-based image analysis-based trough modelling workflow exhibits substantial interoperability across the terrain while producing promising classification accuracies. From an Arctic earth science perspective, the mapped troughs combined with the ArcticDEM can allow hydrological assessments of lateral connectivity of the rapidly changing Arctic tundra landscape, and repeated mapping can allow us to track fine-scale changes across large regions and that has potentially major implications on larger riverine systems.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs13040558