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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Detalles Bibliográficos
Autores principales: Bhuiyan, Md Abul Ehsan, Witharana, Chandi, Liljedahl, Anna K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321207/
https://www.ncbi.nlm.nih.gov/pubmed/34460534
http://dx.doi.org/10.3390/jimaging6120137

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321207/
https://www.ncbi.nlm.nih.gov/pubmed/34460534
http://dx.doi.org/10.3390/jimaging6120137

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