Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019
The potential for oil and gas operations in the Arctic National Wildlife Refuge has accelerated the need to be able to delineate current snow conditions andpredict future snow distributions. Such knowledge could prove essential for both planning and management of any resource development operations....
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NSF Arctic Data Center
2020
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Online Access: | https://dx.doi.org/10.18739/a2mc8rh1w https://arcticdata.io/catalog/view/doi:10.18739/A2MC8RH1W |
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ftdatacite:10.18739/a2mc8rh1w 2023-05-15T14:59:25+02:00 Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 Parr, Charles Sturm, Matthew Larsen, Christopher 2020 text/xml https://dx.doi.org/10.18739/a2mc8rh1w https://arcticdata.io/catalog/view/doi:10.18739/A2MC8RH1W en eng NSF Arctic Data Center snow dataset Dataset 2020 ftdatacite https://doi.org/10.18739/a2mc8rh1w 2021-11-05T12:55:41Z The potential for oil and gas operations in the Arctic National Wildlife Refuge has accelerated the need to be able to delineate current snow conditions andpredict future snow distributions. Such knowledge could prove essential for both planning and management of any resource development operations. Our research combined extensive measurements of snow depth on the ground with aerial photogrammetric mapping in April 2018 and again in April 2019, bothtimes near peak snow depth. Maps were calibrated and validated using thousands of ground depth measurements. The two snow depth maps hosted here represent two years of near peak snow depth from a swath in the Camden Bay area of the refuge. To produce the maps, we: (1) conducted an airborne survey (snow-free) in June that was used to produce a snow-free digital elevation model (DEM) for each swath, (2) conducted airborne surveys at near-peak snow cover each April that were used to create digital surface models (DSMs) of the snow cover, then (3) generated annual high resolution (1 meter(m)) snow depth maps by subtracting the snow-free DEM from the DSMs. Acquiring the snow-free DEM required careful timing because tundra plants leaf out before all snowdrifts melt. The snow depth maps were field-validated and adjusted using thousands of ground-based probe measurements collected concurrently with the airborne surveys. Maps are raster data GeoTIFF file formats where each pixel is one by one meter square. Dataset Arctic Tundra Alaska DataCite Metadata Store (German National Library of Science and Technology) Arctic |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
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language |
English |
topic |
snow |
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snow Parr, Charles Sturm, Matthew Larsen, Christopher Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
topic_facet |
snow |
description |
The potential for oil and gas operations in the Arctic National Wildlife Refuge has accelerated the need to be able to delineate current snow conditions andpredict future snow distributions. Such knowledge could prove essential for both planning and management of any resource development operations. Our research combined extensive measurements of snow depth on the ground with aerial photogrammetric mapping in April 2018 and again in April 2019, bothtimes near peak snow depth. Maps were calibrated and validated using thousands of ground depth measurements. The two snow depth maps hosted here represent two years of near peak snow depth from a swath in the Camden Bay area of the refuge. To produce the maps, we: (1) conducted an airborne survey (snow-free) in June that was used to produce a snow-free digital elevation model (DEM) for each swath, (2) conducted airborne surveys at near-peak snow cover each April that were used to create digital surface models (DSMs) of the snow cover, then (3) generated annual high resolution (1 meter(m)) snow depth maps by subtracting the snow-free DEM from the DSMs. Acquiring the snow-free DEM required careful timing because tundra plants leaf out before all snowdrifts melt. The snow depth maps were field-validated and adjusted using thousands of ground-based probe measurements collected concurrently with the airborne surveys. Maps are raster data GeoTIFF file formats where each pixel is one by one meter square. |
format |
Dataset |
author |
Parr, Charles Sturm, Matthew Larsen, Christopher |
author_facet |
Parr, Charles Sturm, Matthew Larsen, Christopher |
author_sort |
Parr, Charles |
title |
Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
title_short |
Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
title_full |
Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
title_fullStr |
Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
title_full_unstemmed |
Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 |
title_sort |
camden bay snow depth maps: arctic national wildlife refuge, alaska, 2018 and 2019 |
publisher |
NSF Arctic Data Center |
publishDate |
2020 |
url |
https://dx.doi.org/10.18739/a2mc8rh1w https://arcticdata.io/catalog/view/doi:10.18739/A2MC8RH1W |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Tundra Alaska |
genre_facet |
Arctic Tundra Alaska |
op_doi |
https://doi.org/10.18739/a2mc8rh1w |
_version_ |
1766331521586692096 |