Vegetation cover and volume estimates in semi-arid rangelands using LiDAR and hyperspectral data

Sagebrush covers 1.1 x 106 km2 of North American rangelands and is an important cover type for many species. Like most vegetation, sagebrush cover and height varies across the landscape. Accurately mapping this variation is important for certain species, such as the greater sage-grouse, where sagebrush percent cover, visual cover and height are important characteristics for habitat selection. Cover and height are also important factors when trying to estimate rangeland biomass, which is an indicator of forage potential, species dominance and hydrologic function. Several studies have investigated the ability of remote sensing to accurately map vegetation cover, height and volume using a variety of remote sensing technologies. However, no known studies have used a combined spectral and spatial approach for integrative mapping of these characteristics. We demonstrate the ability of terrestrial laser scanning (TLS), airborne Light Detection and Ranging (LiDAR), hyperspectral imagery, and Object Based Image Analysis (OBIA) to accurately estimate sagebrush cover, height and biomass metrics for semi-arid rangeland environments.