Improving the estimation of carbon stocks and fluxes in semi-arid ecosystems of the southwestern US using full-waveform lidar measurements

Marcy E. Litvak, University of New Mexico, mlitvak@unm.edu
Amy Neuenschwander, University of Texas, amy@csr.utexas.edu (Presenter)

The magnitude of carbon fluxes through arid and semi-arid ecosystems is considered modest, but integrated globally (~40% of the global surface) the total carbon stored is almost twice that in temperate forest ecosystems. The purpose of this project is to reduce uncertainties regarding regional carbon dynamics in the Southwestern US by combining a more accurate estimate of vegetation structure using full-waveform lidar to direct measurements of ecosystem-atmosphere carbon exchange across a network of eight eddy covariance tower sites in TX and NM. Lidar remote sensing has become a critical instrument for obtaining information on vegetation structure and a number of studies have tested the use of waveform lidar for characterizing structure and estimating above-ground biomass via height-diameter allometric relationships in temperate and tropical forests. However, in semi-arid environments, the dominant species exhibit more complex allometric relationships due to the multi-stemmed architecture at the base of the tree. We will investigate how laser waveform derived parameters can provide a more accurate estimation of vegetation structure (above-ground biomass, height and leaf area) across a range of semi-arid ecosystems, providing a critical test of the potential of space-based lidar in these environments. Full-waveform lidar data were flown over an Oak/Juniper savanna (Freeman Ranch, TX) in October 2010 and additional waveform lidar data will be flown in September 2011 across an elevation gradient (e.g. creosote scrub to montane conifer) in NM. Metrics derived from the waveform lidar will be regressed against field measured parameters such as dbh, canopy height, basal height, and above ground biomass. Using a model-data fusion (MDF) framework, we will use lidar-derived vegetation structure to improve estimates of regional carbon stocks and make predictions about the response of C dynamics in semi-arid ecosystems to changing climate and disturbance. Here, we present early results from Freeman Ranch.

Presentation Type:  Poster

Session:  Other   (Tue 11:30 AM)

Associated Project(s): 

• Litvak, Marcy: Improving the estimation of carbon stocks and fluxes in semi-arid ecosystems of the southwestern US using full-waveform lidar measurements ...details
• Neuenschwander, Amy: INVESTIGATIONS AND ERROR ANALYSIS OF VEGETATION STRUCTURE RETRIEVAL ALGORITHMS FROM SPACEBORNE LASER ALTIMETRY FOR THE DESDynI MISSION ...details

Poster Location ID: 261