Sunday, 14 August 2016

Estimation of big sagebrush leaf area index with terrestrial laser scanning

Published Date

February 2016, Vol.61:815–821, doi:10.1016/j.ecolind.2015.10.034

Title

Estimation of big sagebrush leaf area index with terrestrial laser scanning

Author

Peter J. Olsoy^a,1^,

Jessica J. Mitchell^b^,

Delphis F. Levia^c^,

Patrick E. Clark^d^,

Nancy F. Glenn^a,^,

aBoise State University, Department of Geosciences, Boise Center Aerospace Lab, 1910 University Drive, Boise, ID 83725, USA
bAppalachian State University, Department of Geography and Planning, P.O. Box 32066, Boone, NC 28608, USA
cUniversity of Delaware, Departments of Geography and Plant & Soil Sciences, Newark, DE 19716, USA
dUSDA Agricultural Research Service, 800 Park Blvd, Suite 105, Boise, ID 83712, USA

Received 7 January 2015. Revised 8 October 2015. Accepted 13 October 2015. Available online 10 November 2015.

Highlights

•
Data from terrestrial laser scanning (TLS) were used to estimate sagebrush LAI.
•
TLS-based convex-hull volume strongly predicted LAI (r² = 0.76).
•
Canopy cover from TLS strongly predicted LAI (r² = 0.73).
•
Specific leaf area of sagebrush differed significantly between sites (P = 0.025).
•
TLS is a promising tool to estimate shrub LAI in terrestrial ecosystems.

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), 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.