Estimation of big sagebrush leaf area index with terrestrial laser scanning

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), and compared favorably to point-intercept sampling (r² = 0.78), a field-based method used in rangelands. 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.