|OLSOY, PETER - Idaho State University|
|GLENN, NANCY - Idaho State University|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/16/2013
Publication Date: 3/1/2014
Citation: Olsoy, P.J., Glenn, N.F., Clark, P. 2014. Estimating sagebrush biomass using terrestrial laser scanning (TLS). Remote Sensing of Environment. 67:224-228. DOI: 10.2111/REM-D-12-00186.1.
Interpretive Summary: Sagebrush (Artemisia tridentata) provides an extensive, long-term carbon storage pool as well as important habitat to many wildlife species; consequently, there is a critical but unfulfilled need for repeated, non-destructive monitoring of sagebrush biomass across extensive rangelands. In this study, aboveground biomass estimates for 30 sagebrush in Reynolds Creek Experimental Watershed, Idaho, USA were acquired using Terrestrial Laser Scanning (TLS) and contrasted with estimates acquired by point-intercept (i.e., a non-destruction field sampling technique) and measurements collected by destructive harvest (i.e., clip, oven-dry, and weigh). Accuracy of TLS-derived total and green biomass (i.e., leaves and green stems only) estimates was comparable to and even exceeded that of estimates derived with point-intercept sampling. Combined with potential increases in time efficiency and flexibility relative to traditional field techniques like point-intercept sampling, these accuracy evaluations confirm that TLS is a promising new approach for repeated, non-destruction monitoring of extensive sagebrush-dominated rangelands.
Technical Abstract: The impacts of climate change, including changing fire frequency and intensity and the spread of invasive species have led to a rapidly changing habitat for sagebrush (Artemisia tridentata). Monitoring the change and distribution of suitable habitat and fuel loads is an important aspect of sagebrush management under future climate conditions. Biomass can be used to monitor sagebrush health over time and quantify carbon storage. Commonly-used methods to determine sagebrush biomass include destructive and point-intercept sampling, both of which can be expensive and time consuming. LiDAR (light detection and ranging) techniques, including airborne laser scanning (ALS) and terrestrial laser scanning (TLS), have become valuable tools for assessing biomass in forested environments but have not been as well developed for sagebrush steppe. This study used TLS to estimate biomass of 30 sagebrush in Reynolds Creek Experimental Watershed, Idaho, USA. The accuracy of the TLS-derived biomass was assessed and contrasted with the accuracy of point-intercept sampling using regression analysis and destructive sampling. TLS-derived volume had a slightly higher coefficient of determination (R2) when predicting total biomass compared to point-intercept sampling (0.89 and 0.86, respectively). Green biomass, or production, was also determined and TLS-derived volume had an R2 of 0.87 with a single outlier removed (0.69 when included) while the point-intercept method resulted in an R2 of 0.71. This study explores a promising new method to monitor biomass across the landscape through space and time. TLS can rapidly scan large field areas during peak primary production, and extract vegetation characteristics such as biomass at a later date. Future work should focus on making this method independent of sensor, scan distance, scan number, and study area.