Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016
A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current da...
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ftosti:oai:osti.gov:1418854 2023-07-30T04:01:27+02:00 Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 Langford, Zachary Kumar, Jitendra Hoffman, Forrest Iversen, Colleen Breen, Amy 2021-07-15 application/pdf http://www.osti.gov/servlets/purl/1418854 https://www.osti.gov/biblio/1418854 https://doi.org/10.5440/1418854 unknown http://www.osti.gov/servlets/purl/1418854 https://www.osti.gov/biblio/1418854 https://doi.org/10.5440/1418854 doi:10.5440/1418854 54 Environmental Sciences 2021 ftosti https://doi.org/10.5440/1418854 2023-07-11T09:23:54Z A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current data is located in the Kougarok watershed but we plan to expand this over the Seward Peninsula. Dataset DOI:10.5440/1418854; https://doi.org/10.5440/1418854 Other/Unknown Material Arctic Seward Peninsula Alaska SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic |
institution |
Open Polar |
collection |
SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 Environmental Sciences |
spellingShingle |
54 Environmental Sciences Langford, Zachary Kumar, Jitendra Hoffman, Forrest Iversen, Colleen Breen, Amy Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
topic_facet |
54 Environmental Sciences |
description |
A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current data is located in the Kougarok watershed but we plan to expand this over the Seward Peninsula. Dataset DOI:10.5440/1418854; https://doi.org/10.5440/1418854 |
author |
Langford, Zachary Kumar, Jitendra Hoffman, Forrest Iversen, Colleen Breen, Amy |
author_facet |
Langford, Zachary Kumar, Jitendra Hoffman, Forrest Iversen, Colleen Breen, Amy |
author_sort |
Langford, Zachary |
title |
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
title_short |
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
title_full |
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
title_fullStr |
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
title_full_unstemmed |
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016 |
title_sort |
remote sensing-based, 5-m, vegetation distributions, kougarok study site, seward peninsula, alaska, ca. 2009 - 2016 |
publishDate |
2021 |
url |
http://www.osti.gov/servlets/purl/1418854 https://www.osti.gov/biblio/1418854 https://doi.org/10.5440/1418854 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Seward Peninsula Alaska |
genre_facet |
Arctic Seward Peninsula Alaska |
op_relation |
http://www.osti.gov/servlets/purl/1418854 https://www.osti.gov/biblio/1418854 https://doi.org/10.5440/1418854 doi:10.5440/1418854 |
op_doi |
https://doi.org/10.5440/1418854 |
_version_ |
1772812185222774784 |