Summary & Purpose
The dataset is a collection of 1m resolution snow depth, elevation, aspect, slope, canopy percent cover, canopy height, foliage height diversity (FHD) with 0.5 m, 1 m, and 2 m voxel sizes. We processed lidar data of Grand Mesa, Colorado, representing a data collection effort by the NASA SnowEx campaign. Using the data we investigate how structural diversity and topography affect snow depth patterns. Snow depth is computed by snow-off and snow-on dataset from September 2016 and February 2020, respectively. Snow-off lidar data were collected by the Airborne Snow Observatory (ASO), lidar system created by NASA/JPL. Snow-on lidar data are provided by Quantum Spatial as a part of the NASA SnowEx (https://snow.nasa.gov/campaigns/snowex) campaign in 2020.
Date of Publication or Submission
7-11-2022
Recommended Citation
Hojatimalekshah, Ahmad; Glenn, Nancy F.; and Enterkine, Josh. (2022). Dataset for 1 m Resolution Snow Depth, Topographical, and Vegetation Structural Metrics [Data set]. Retrieved from https://doi.org/10.18122/bcal_data.6.boisestate
DOI
https://doi.org/10.18122/bcal_data.6.boisestate
Funding Citation
This research has been supported by NASA, grant number 80NSSC18K0955.
Single Dataset or Series?
Dataset
Data Format
Data is provided as GeoTIFF (*.tif) formatted file; *.tfw; and *.txt
Data Attributes
The data set is in 1m resolution from Grand Mesa, Colorado, USA. The Image dimension is 3500*17000*9, which the first band of the image is snow depth, and other 8 bands are elevation, aspect, slope, canopy percent cover, canopy height, and FHD0.5, FHD1.0, and FHD 2.0 respectively. Airborne lidar data products are from the NASA Airborne Snow Observatory (ASO) and Quantum collected on two campaigns during 2016-2017, and 2019-2020. Using the data, we attempt to estimate snow depth using topographical features, and vegetation structure in a deep learning model. Airborne lidar data were collected during two SnowEx campaigns in September 2016 (snow-off), and prior to melt (and during the accumulation season) in February 2020 (snow-on). We computed snow depth by applying the M3C2 method used in Hojatimalekshah et al. (2021), achieving a relative vertical accuracy of 7 cm based on the maximum standard deviation. FHD are computed using BCAL lidar tools package (https://www.boisestate.edu/bcal/resources/bcal-lidar-tools/) in ENVI. Topographic, and vegetation metrics computed for our study use the snow-off data. To calculate the snow depth we transformed the 2016 snow-off vertical datum into the same datum as the 2020 snow-on data (https://vdatum.noaa.gov/).
Reference Hojatimalekshah A, Uhlmann Z, Glenn NF, et al. 2021.
Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning. The Cryosphere 15: 2187–209.
Map Area
4325000.5000m N
Map Area
4321500.5000m N
Map Area
741500.2500m E
Map Area
758499.2500m E
Map Area Coordinate System
Projection : UTM, Zone 12 North
Datum: North America 1983
Vertical Datum: NAVD88
Time Period
Topographical and vegetation layers are from Sep-26, 2016 and Snow depth is from Feb-1st, 2020
Privacy and Confidentiality Statement
Boise State is explicitly compliant with federal and state laws surrounding data privacy including the protection of personal financial information through the Gramm-Leach-Bliley Act, personal medical information through HIPAA, HITECH and other regulations. All human subject data (e.g., surveys) has been collected and managed only by personnel with adequate human subject protection certification.
Use Restrictions
Users are free to share, copy, distribute and use the dataset; to create or produce works from the dataset; to adapt, modify, transform and build upon the dataset as long as the user attributes any public use of the dataset, or works produced from the dataset, referencing the author(s) and DOI link. For any use or redistribution of the dataset, or works produced from it, the user must make clear to others the license of the dataset and keep intact any notices on the original dataset.
Disclaimer of Warranty
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