Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018
list("Snow is a crucial resource for billions of people on Earth. We proposed a study of snow drifts. Drifts can comprise more than half of the local snow water equivalent (SWE) and play a large and widely overlooked role in snow hydrology. They melt slowly, resulting in a crucial shift in the...
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ftdatacite:10.18739/a21r6n171 2023-05-15T15:19:33+02:00 Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 Parr, Charles Sturm, Matthew Larsen, Christopher 2020 text/xml https://dx.doi.org/10.18739/a21r6n171 https://arcticdata.io/catalog/view/doi:10.18739/A21R6N171 en eng NSF Arctic Data Center snow dataset Dataset 2020 ftdatacite https://doi.org/10.18739/a21r6n171 2021-11-05T12:55:41Z list("Snow is a crucial resource for billions of people on Earth. We proposed a study of snow drifts. Drifts can comprise more than half of the local snow water equivalent (SWE) and play a large and widely overlooked role in snow hydrology. They melt slowly, resulting in a crucial shift in the timing of water delivery that syncs snow melt directly to agricultural and ecosystem needs, yet we know little about drifts on either local or global scales. The overall goal of the research was to better understand the role and importance of snow drifts in hydrology. Using lidar and structure-from-motion (SfM) photogrammetry, we conducted an airborne study of drifts coupled with extensive ground validation in search of preliminary answers to questions on the importance of drifts and the percentage of SWE found in drifts in a variety of terrain types.", "The snow depth maps hosted here represent six years of drift records from northern Alaska and enable the analysis of the relationships between drifts and the surrounding snowcover and the landscape below, as well as drift persistence over time.", "Snow depth mapping was done using airborne SfM photogrammetry (2015 through 2018) and lidar (2012 and 2013) and then adjusted to ground-based probe measurements of snow depth. The area mapped each year over two swaths was about 130 kilometer squared (km^2). 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 m) snow depth maps by subtracting the snow-free DEM from the DSMs. Six such depth maps were produced for each swath between 2012 and 2018, comprising over 600 million individual geospatial snow depth records. 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 141,207 ground-based probe measurements collected concurrently with the airborne surveys.", "There are twelve (12) snow depth raster maps deposited here. Each map represents the near-peak annual snow depth across a swath of Arctic tundra. There are two swaths: CLPX (a zone that was part of a Cold Land Experimental Site - a NASA snow measurement program that rotates through several different field areas) and HV (Happy Valley). Map years include 2012, 2013, 2015, 2016, 2017, and 2018. Maps are raster data GeoTIFF file formats where each pixel is one by one meter square. The file naming convention is *swath*_depth_*DOY*_*YYYY*_corrected_*correction_amount*.tif.") Dataset Arctic Brooks Range Tundra Alaska DataCite Metadata Store (German National Library of Science and Technology) Arctic Happy Valley ENVELOPE(-133.520,-133.520,60.016,60.016) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
snow |
spellingShingle |
snow Parr, Charles Sturm, Matthew Larsen, Christopher Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
topic_facet |
snow |
description |
list("Snow is a crucial resource for billions of people on Earth. We proposed a study of snow drifts. Drifts can comprise more than half of the local snow water equivalent (SWE) and play a large and widely overlooked role in snow hydrology. They melt slowly, resulting in a crucial shift in the timing of water delivery that syncs snow melt directly to agricultural and ecosystem needs, yet we know little about drifts on either local or global scales. The overall goal of the research was to better understand the role and importance of snow drifts in hydrology. Using lidar and structure-from-motion (SfM) photogrammetry, we conducted an airborne study of drifts coupled with extensive ground validation in search of preliminary answers to questions on the importance of drifts and the percentage of SWE found in drifts in a variety of terrain types.", "The snow depth maps hosted here represent six years of drift records from northern Alaska and enable the analysis of the relationships between drifts and the surrounding snowcover and the landscape below, as well as drift persistence over time.", "Snow depth mapping was done using airborne SfM photogrammetry (2015 through 2018) and lidar (2012 and 2013) and then adjusted to ground-based probe measurements of snow depth. The area mapped each year over two swaths was about 130 kilometer squared (km^2). 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 m) snow depth maps by subtracting the snow-free DEM from the DSMs. Six such depth maps were produced for each swath between 2012 and 2018, comprising over 600 million individual geospatial snow depth records. 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 141,207 ground-based probe measurements collected concurrently with the airborne surveys.", "There are twelve (12) snow depth raster maps deposited here. Each map represents the near-peak annual snow depth across a swath of Arctic tundra. There are two swaths: CLPX (a zone that was part of a Cold Land Experimental Site - a NASA snow measurement program that rotates through several different field areas) and HV (Happy Valley). Map years include 2012, 2013, 2015, 2016, 2017, and 2018. Maps are raster data GeoTIFF file formats where each pixel is one by one meter square. The file naming convention is *swath*_depth_*DOY*_*YYYY*_corrected_*correction_amount*.tif.") |
format |
Dataset |
author |
Parr, Charles Sturm, Matthew Larsen, Christopher |
author_facet |
Parr, Charles Sturm, Matthew Larsen, Christopher |
author_sort |
Parr, Charles |
title |
Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
title_short |
Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
title_full |
Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
title_fullStr |
Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
title_full_unstemmed |
Landscape Scale Snow Depth Maps: Brooks Range Foothills, Alaska, 2012-2018 |
title_sort |
landscape scale snow depth maps: brooks range foothills, alaska, 2012-2018 |
publisher |
NSF Arctic Data Center |
publishDate |
2020 |
url |
https://dx.doi.org/10.18739/a21r6n171 https://arcticdata.io/catalog/view/doi:10.18739/A21R6N171 |
long_lat |
ENVELOPE(-133.520,-133.520,60.016,60.016) |
geographic |
Arctic Happy Valley |
geographic_facet |
Arctic Happy Valley |
genre |
Arctic Brooks Range Tundra Alaska |
genre_facet |
Arctic Brooks Range Tundra Alaska |
op_doi |
https://doi.org/10.18739/a21r6n171 |
_version_ |
1766349741937917952 |