Developing Tree-scale Biomass for Fire Modeling, Carbon Measurement and Habitat Assessment

Lead Investigator: Carl Seielstad, University of Montana

Using lasers to measure ranges between aircraft and the earth surface, LiDAR (Light Detection and Ranging) represents an advanced remote sensing technology in the domain of forest measurements.  Many universities, corporations, federal and state agencies have begun to explore LiDAR technology on research forests and industrial timber lands as a potential  means of forest inventory.  The National Center for Landscape Fire Analysis in Montana's College of Forestry and Conservation acquired LiDAR data for the Lubrecht Experimental Forest (LEF) in June 2005.  The P.I. is leveraging this investment by establishing a research and development program targeted at identification and measurement of individual trees with the goal of quantifying biomass at a tree scale.  The P.I. proposes to (1) develop tree-level relationships between laser altimetry-derived height, crown width, and dbh; (2) identify the locations of individual tree stems; and (3) attribute those stems with foliage, branch and stem biomass.  Core research areas include stem ID in dense and/or multi-aged stands, species identification, and quantification of the error of estimates at the tree scale.  The purpose of this endeavor is to develop a baseline validation project that will support spatially explicit fuels characterizations, carbon estimation, and habitat assessment.