CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models

This repository contains data and code used in the paper "Rapid machine-learning-based extraction and measurement of ice wedge polygons in high-resolution digital elevation models" by Abolt et al . in The Cryosphere (2019). See the included README file for instructions on usage.

Bibliographic Details
Main Authors: Abolt, Charles J, Young, Michael H, Atchley, Adam L, Wilson, Cathy J
Format: Other/Unknown Material
Language:English
Published: Zenodo 2019
Subjects:
Ice
Online Access:https://doi.org/10.5821/zenodo.2537167
id ftzenodo:oai:zenodo.org:2537167
record_format openpolar
spelling ftzenodo:oai:zenodo.org:2537167 2024-09-15T18:11:26+00:00 CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models Abolt, Charles J Young, Michael H Atchley, Adam L Wilson, Cathy J 2019-01-25 https://doi.org/10.5821/zenodo.2537167 eng eng Zenodo https://doi.org/10.5194/tc-13-237-2019 https://doi.org/10.5821/zenodo.2537167 oai:zenodo.org:2537167 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode ice wedge polygon permafrost thermokarst deep learning machine learning convolutional neural network info:eu-repo/semantics/other 2019 ftzenodo https://doi.org/10.5821/zenodo.253716710.5194/tc-13-237-2019 2024-07-26T09:55:03Z This repository contains data and code used in the paper "Rapid machine-learning-based extraction and measurement of ice wedge polygons in high-resolution digital elevation models" by Abolt et al . in The Cryosphere (2019). See the included README file for instructions on usage. Other/Unknown Material Ice permafrost Thermokarst wedge* Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic ice wedge polygon
permafrost
thermokarst
deep learning
machine learning
convolutional neural network
spellingShingle ice wedge polygon
permafrost
thermokarst
deep learning
machine learning
convolutional neural network
Abolt, Charles J
Young, Michael H
Atchley, Adam L
Wilson, Cathy J
CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
topic_facet ice wedge polygon
permafrost
thermokarst
deep learning
machine learning
convolutional neural network
description This repository contains data and code used in the paper "Rapid machine-learning-based extraction and measurement of ice wedge polygons in high-resolution digital elevation models" by Abolt et al . in The Cryosphere (2019). See the included README file for instructions on usage.
format Other/Unknown Material
author Abolt, Charles J
Young, Michael H
Atchley, Adam L
Wilson, Cathy J
author_facet Abolt, Charles J
Young, Michael H
Atchley, Adam L
Wilson, Cathy J
author_sort Abolt, Charles J
title CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
title_short CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
title_full CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
title_fullStr CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
title_full_unstemmed CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
title_sort cnn-watershed: a machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models
publisher Zenodo
publishDate 2019
url https://doi.org/10.5821/zenodo.2537167
genre Ice
permafrost
Thermokarst
wedge*
genre_facet Ice
permafrost
Thermokarst
wedge*
op_relation https://doi.org/10.5194/tc-13-237-2019
https://doi.org/10.5821/zenodo.2537167
oai:zenodo.org:2537167
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5821/zenodo.253716710.5194/tc-13-237-2019
_version_ 1810449025870069760