|OLSOY, PETER - Boise State University|
|MITCHELL, JESSICA - Appalachian State University|
|GLENN, NANCY - Boise State University|
|LEVIA, DELPHIS - University Of Delaware|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/22/2014
Publication Date: 10/7/2014
Citation: Clark, P., Olsoy, P.J., Mitchell, J.J., Glenn, N.F., Levia, D.F. 2014. Estimation of big sagebrush leaf area index with terrestrial laser scanning. Meeting Abstract.
Interpretive Summary: Arid and semiarid ecosystems, including grasslands, shrublands, and savannas, dominate about 40% of the Earth’s land surface. Global models of carbon, water, and nutrient cycles are essential to predict the effects of climate change and better understand its effects on semiarid vegetation communities. Traditionally, vegetation structure and function is monitored using field-derived metrics such as percent cover, species composition, primary productivity, and biomass. Leaf area index (LAI), defined as the one-sided area of green leaves per unit ground area, is an important variable for photosynthesis, evapotranspiration, and energy balance models. LAI is frequently estimated with remote sensing techniques, providing users with an easily scalable measure of vegetation structure. We used terrestrial laser scanning (TLS) to measure structural variables such as shrub height, canopy cover, and volume for 45 Wyoming big sagebrush plants sampled across three study sites in the Snake River Plain. The TLS-derived variables were regressed against sagebrush LAI derived from specific leaf area. Canopy cover proved to be a good predictor of LAI (r2 = 0.73), as did convex hull volume (r2 = 0.76). However, TLS-derived shrub height was a relatively poor predictor (r2 = 0.47) and did not explain any additional variation when combined with canopy cover (r2 = 0.73). These results suggest that TLS is a good predictor of LAI at the shrub-level. Further work should examine the potential to estimate LAI at the plot-level (i.e., hectare).
Technical Abstract: A remote-sensing technique is need to bridge the gap between airborne laser scanning (ALS) and ground-based field techniques for accurately assessing leaf area index (LAI) in sparsely vegetated landscapes like sagebrush steppe. Terrestrial laser scanning (TLS) was used to measure structural variables such as shrub height, canopy cover, and volume for Wyoming big sagebrush plants sampled at three study sites in the Snake River Plain of southern Idaho. The TLS-derived variables, canopy cover and canopy volume, were both good predictors of sagebrush LAI. This study confirms that TLS provides an opportunity to scale between intensive, ground-based measurements and coarser assessments of vegetation made with airborne and satellite remote sensing.