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Title: Estimation of big sagebrush leaf area index with terrestrial laser scanning

Author
item OLSOY, PETER - BOISE STATE UNIVERSITY
item MITCHELL, JESSICA - APPALACHIAN STATE UNIVERSITY
item LEVIA, DELPHIS - UNIVERSITY OF DELAWARE
item Clark, Pat
item GLENN, NANCY - BOISE STATE UNIVERSITY

Submitted to: Ecological Indicators
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/13/2015
Publication Date: 11/10/2015
Citation: Olsoy, P.J., Mitchell, J., Levia, D.F., Clark, P., Glenn, N.F. 2015. Estimation of big sagebrush leaf area index with terrestrial laser scanning. Ecological Indicators. 61:815-821.

Interpretive Summary: Shrub-dominated rangelands potentially play a substantial role in carbon dynamics associated with global climate change; however, data for shrub leaf area index (LAI) are scarce due to costs and technique limitations. We tested terrestrial laser scanning (TLS) techniques to estimate LAI using structural variables such as height, canopy cover, and volume for 42 Wyoming big sagebrush plants (Artemisia tridentata subsp. wyomingensis Beetle & Young) distributed across three study sites in the Snake River Plain, Idaho, USA. A convex-hull approach to estimating shrub volume from TLS data was found to be a strong predictor of LAI. Given its efficiency and relative ease-of-use, TLS is a promising tool for estimating shrub LAI and addressing questions regarding terrestrial ecosystem contributions to climate change.

Technical Abstract: Accurate monitoring and quantification of the structure and function of semiarid ecosystems is necessary to improve carbon and water flux models that help describe how these systems will respond in the future. The leaf area index (LAI, m2 m-2) is an important indicator of energy, water, and carbon exchange between vegetation and the atmosphere. Remote sensing techniques are frequently used to estimate LAI, and can provide users with scalable measurements of vegetation structure and function. We tested terrestrial laser scanning (TLS) techniques to estimate LAI using structural variables such as height, canopy cover, and volume for 42 Wyoming big sagebrush (Artemisia tridentata subsp. wyomingensis Beetle & Young) shrubs across three study sites in the Snake River Plain, Idaho, USA. The TLS-derived variables were regressed against sagebrush LAI estimates calculated using specific leaf area measurements, and compared with point-intercept sampling, a field method of estimating LAI. Canopy cover estimated with the TLS data proved to be a good predictor of LAI (r2 = 0.73). Similarly, a convex hull approach to estimate volume of the shrubs from the TLS data also strongly predicted LAI (r2 = 0.76). These results, coupled with the relative ease-of-use of TLS, suggest that TLS is a promising tool for measuring LAI at the shrub-level. Further work should examine the structural measures in other similar shrublands that are relevant for upscaling LAI to the plot-level (i.e., hectare) using data from TLS and/or airborne laser scanning and to regional levels using satellite-based remote sensing.