NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters
Abstract
Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information). These LiDAR data are the primary data that were provided by NEON including LAZ files of a classified point cloud, and geotifs of a digital surface elevation model, digital terrain elevation model, and a canopy height model at 1 m resolution with a height threshold of > 2 m. Raster files can also be found on Google Earth Engine: https://code.earthengine.google.com/5c96bbc96ffd50e3c8b1433b34a0bb86.
- Authors:
-
- Lawrence Berkeley National Laboratory
- Publication Date:
- Other Number(s):
- paf_361
- DOE Contract Number:
- AC02-05CH11231
- Research Org.:
- Watershed Function SFA
- Sponsoring Org.:
- U.S. DOE > Office of Science > Biological and Environmental Research (BER)
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Canopy Height Model; Digital Surface Elevation; Digital Terrain Model; EARTH SCIENCE > BIOSPHERE > VEGETATION; EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY; EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM); LiDAR Point Cloud; Lidar; NEON AOP; NEON Campaign 2018; Remote Sensing; canopy height; canopy_height
- OSTI Identifier:
- 1617203
- DOI:
- https://doi.org/10.15485/1617203
Citation Formats
Goulden, Tristan, Hass, Bridget, Brodie, Eoin, Chadwick, K. Dana, Falco, Nicola, Maher, Kate, Wainwright, Haruko, and Williams, Kenneth. NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters. United States: N. p., 2019.
Web. doi:10.15485/1617203.
Goulden, Tristan, Hass, Bridget, Brodie, Eoin, Chadwick, K. Dana, Falco, Nicola, Maher, Kate, Wainwright, Haruko, & Williams, Kenneth. NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters. United States. doi:https://doi.org/10.15485/1617203
Goulden, Tristan, Hass, Bridget, Brodie, Eoin, Chadwick, K. Dana, Falco, Nicola, Maher, Kate, Wainwright, Haruko, and Williams, Kenneth. 2019.
"NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters". United States. doi:https://doi.org/10.15485/1617203. https://www.osti.gov/servlets/purl/1617203. Pub date:Tue Dec 31 23:00:00 EST 2019
@article{osti_1617203,
title = {NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters},
author = {Goulden, Tristan and Hass, Bridget and Brodie, Eoin and Chadwick, K. Dana and Falco, Nicola and Maher, Kate and Wainwright, Haruko and Williams, Kenneth},
abstractNote = {Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information). These LiDAR data are the primary data that were provided by NEON including LAZ files of a classified point cloud, and geotifs of a digital surface elevation model, digital terrain elevation model, and a canopy height model at 1 m resolution with a height threshold of > 2 m. Raster files can also be found on Google Earth Engine: https://code.earthengine.google.com/5c96bbc96ffd50e3c8b1433b34a0bb86.},
doi = {10.15485/1617203},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Dec 31 23:00:00 EST 2019},
month = {Tue Dec 31 23:00:00 EST 2019}
}
