Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types

Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types

We developed a high-throughput mapping workflow, which centers on deep learning (DL) convolutional neural network (CNN) algorithms on high-performance distributed computing resources, to automatically characterize ice-wedge polygons (IWPs) from sub-meter resolution commercial satellite imagery. We a...

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Bibliographic Details
Main Authors: Md Abul Ehsan Bhuiyan, Chandi Witharana, Anna K. Liljedahl
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Journal of Imaging
Subjects:
permafrost
Arctic
deep learning
tundra
ice-wedge polygon
Mask R-CNN
Online Access:https://www.mdpi.com/2313-433X/6/12/137

Internet

https://www.mdpi.com/2313-433X/6/12/137

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