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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Bibliographic Details
Main Authors: Charles Parr, Matthew Sturm, Christopher Larsen
Format: Dataset
Language:unknown
Published: Arctic Data Center 2020
Subjects:
Online Access:https://doi.org/10.18739/A2MC8RH1W
id dataone:doi:10.18739/A2MC8RH1W
record_format openpolar
spelling dataone:doi:10.18739/A2MC8RH1W 2024-06-03T18:46:34+00:00 Camden Bay Snow Depth Maps: Arctic National Wildlife Refuge, Alaska, 2018 and 2019 Charles Parr Matthew Sturm Christopher Larsen Arctic National Wildlife Refuge, Alaska ENVELOPE(-144.81618,-144.75183,69.96083,69.78058) BEGINDATE: 2018-01-01T00:00:00Z ENDDATE: 2019-01-01T00:00:00Z 2020-01-01T00:00:00Z https://doi.org/10.18739/A2MC8RH1W unknown Arctic Data Center snow Dataset 2020 dataone:urn:node:ARCTIC https://doi.org/10.18739/A2MC8RH1W 2024-06-03T18:16:34Z 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 Arctic Data Center (via DataONE) Arctic ENVELOPE(-144.81618,-144.75183,69.96083,69.78058)
institution Open Polar
collection Arctic Data Center (via DataONE)
op_collection_id dataone:urn:node:ARCTIC
language unknown
topic snow
spellingShingle snow
Charles Parr
Matthew Sturm
Christopher Larsen
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 Charles Parr
Matthew Sturm
Christopher Larsen
author_facet Charles Parr
Matthew Sturm
Christopher Larsen
author_sort Charles Parr
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 Arctic Data Center
publishDate 2020
url https://doi.org/10.18739/A2MC8RH1W
op_coverage Arctic National Wildlife Refuge, Alaska
ENVELOPE(-144.81618,-144.75183,69.96083,69.78058)
BEGINDATE: 2018-01-01T00:00:00Z ENDDATE: 2019-01-01T00:00:00Z
long_lat ENVELOPE(-144.81618,-144.75183,69.96083,69.78058)
geographic Arctic
geographic_facet Arctic
genre Arctic
Tundra
Alaska
genre_facet Arctic
Tundra
Alaska
op_doi https://doi.org/10.18739/A2MC8RH1W
_version_ 1800868016451223552