Estimating Above Ground Biomass using LiDAR in the Northcoast Redwood Forests
Abstract
In recent years, LiDAR (Light Intensity Detection Amplification and Ranging) is increasingly being used in estimating biophysical parameters related to forested environments. The main goal of the project is to estimate long-term biomass accumulation and carbon sequestration potential of the redwoods ecosystem. The project objectives are aimed at providing an assessment of carbon pools within the redwood ecosystem. Specifically, we intend to develop a relational model based on LiDAR-based canopy estimates and extensive ground-based measurements available for the old-growth redwood forest located within the Prairie Creek Redwoods State Park, CA. Our preliminary analysis involved developing a geospatial database, including LiDAR data collected in 2007 for the study site, and analyzing the data using USFS Fusion software. The study area comprised of a 12-acres section of coastal redwood (Sequoia sempervirens) in the Prairie Creek Redwoods State Park, located in Orick, CA. A series of analytical steps were executed using the USFS FUSION software to produce some intermediate data such as bare earth model, canopy height model, canopy coverage model, and canopy maxima treelist. Canopy maxima tree tops were compared to ground layer to determine height of tree tops. A total of over 1000 trees were estimated, and then with thinning (to eliminate errors due to low vegetation > 3 meters tall), a total of 950 trees were delineated. Ground measurements were imported as a point based shapefile and then compared to the treetop heights created from LiDAR data to the actual ground referenced data. The results were promising as most estimated treetops were within 1-3 meters of the ground measurements and generally within 3-5m of the actual tree height. Finally, we are in the process of applying some allometric equations to estimate above ground biomass using some of the LiDAR-derived canopy metrics.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFM.B33A0395R
- Keywords:
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- 0428 BIOGEOSCIENCES / Carbon cycling;
- 0480 BIOGEOSCIENCES / Remote sensing