This study was designed to determine the utility of a 1-m-resolution hyperspectral sensor to estimate total and live biomass along with the individual biomass of litter, grasses, forbs, sedges, sagebrush, and willow from grassland and riparian communities in Yellowstone National Park, Wyoming. A large number of simple ratio-type vegetation indices (SRTVI) and normalized difference- type vegetation indices (NDTVI) were developed from the hyperspectral data and regressed against ground-collected biomass. Results showed the following: 1) Strong relationships were found between SRTVI or NDTVI and total (R2 = 0.87), live (R2 = 0.84), sedge (R2 = 0.77), and willow (R2 = 0.66) biomass. 2) Weak relationships were found between SRTVI or NDTVI and grass (R2 = 0.39), forb (R2 = 0.16), and litter (R2 = 0.51) biomass, possibly caused by the mixture of spectral signatures with grasses, sedges, and willows along with the variable effect of the litter spectral signature. 3) A weak relationship was found between sagebrush biomass and SRTVI or NDTSI (R2 = 0.3) that was related to interference from sagebrush photosynthetic or nonphotosynthetic branch and twig material, and from the indeterminate spectral signature of sagebrush. This study has shown that hyperspectral imagery at 1-m resolution can result in high correlations and low error estimates for a variety of biomass components in rangelands. This methodology can thus become a very useful tool to estimate rangeland biomass over large areas. The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information. Migrated from OJS platform August 2020 Legacy DOIs that must be preserved: 10.2458/azu_rangelands_v58i5_norland
Scholarly peer-reviewed articles published by the Society for Range Management. Access articles on a rolling-window basis from vol. 1, 1948 up to 5 years from the current year. Formerly Journal of Range Management (JRM). More recent content is available by subscription from SRM.