Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017

The U.S. Geological Survey in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) collected topographic LiDAR surveys of four rivers in Alaska from August 8-9, 2017 to support research related to remote sensing of river discharge. Data were ac...

Full description

Bibliographic Details
Main Authors: Kinzel, Paul J, Legleiter, Carl J, LeWinter, Adam, Gadomski, Peter
Format: Dataset
Language:unknown
Published: U.S. Geological Survey 2019
Subjects:
Cold Regions Research and Engineering Laboratory
Alaska
Online Access:https://dx.doi.org/10.5066/p9iqcvju
https://www.sciencebase.gov/catalog/item/5ae8b775e4b06d9233b8a80c
id ftdatacite:10.5066/p9iqcvju
record_format openpolar
spelling ftdatacite:10.5066/p9iqcvju 2023-05-15T15:55:48+02:00 Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017 Kinzel, Paul J Legleiter, Carl J LeWinter, Adam Gadomski, Peter 2019 https://dx.doi.org/10.5066/p9iqcvju https://www.sciencebase.gov/catalog/item/5ae8b775e4b06d9233b8a80c unknown U.S. Geological Survey dataset Dataset 2019 ftdatacite https://doi.org/10.5066/p9iqcvju 2021-11-05T12:55:41Z The U.S. Geological Survey in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) collected topographic LiDAR surveys of four rivers in Alaska from August 8-9, 2017 to support research related to remote sensing of river discharge. Data were acquired for the Knik, Matanuska, Chena and Salcha Rivers using a Riegl VQ-580 LiDAR. The LiDAR was installed on a Robinson R44 Raven helicopter in a HeliPod that was designed and operated by CRREL. The LiDAR data included as part of this release include: a bare earth digital elevation model (DEM), an intensity or reflectence digital surface model (DSM) both in GeoTiff format, and compressed binary LAS files (LAZ) for each river surveyed. Dataset Cold Regions Research and Engineering Laboratory Alaska DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description The U.S. Geological Survey in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) collected topographic LiDAR surveys of four rivers in Alaska from August 8-9, 2017 to support research related to remote sensing of river discharge. Data were acquired for the Knik, Matanuska, Chena and Salcha Rivers using a Riegl VQ-580 LiDAR. The LiDAR was installed on a Robinson R44 Raven helicopter in a HeliPod that was designed and operated by CRREL. The LiDAR data included as part of this release include: a bare earth digital elevation model (DEM), an intensity or reflectence digital surface model (DSM) both in GeoTiff format, and compressed binary LAS files (LAZ) for each river surveyed.
format Dataset
author Kinzel, Paul J
Legleiter, Carl J
LeWinter, Adam
Gadomski, Peter
spellingShingle Kinzel, Paul J
Legleiter, Carl J
LeWinter, Adam
Gadomski, Peter
Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
author_facet Kinzel, Paul J
Legleiter, Carl J
LeWinter, Adam
Gadomski, Peter
author_sort Kinzel, Paul J
title Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
title_short Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
title_full Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
title_fullStr Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
title_full_unstemmed Topographic LiDAR surveys of rivers in Alaska, August 8-9, 2017
title_sort topographic lidar surveys of rivers in alaska, august 8-9, 2017
publisher U.S. Geological Survey
publishDate 2019
url https://dx.doi.org/10.5066/p9iqcvju
https://www.sciencebase.gov/catalog/item/5ae8b775e4b06d9233b8a80c
genre Cold Regions Research and Engineering Laboratory
Alaska
genre_facet Cold Regions Research and Engineering Laboratory
Alaska
op_doi https://doi.org/10.5066/p9iqcvju
_version_ 1766391291069857792

Similar Items