Browsing Rangeland Ecology & Management, Volume 58, Number 5 (September 2005) by Subjects
Now showing items 1-2 of 2
Hyperspectral One-Meter-Resolution Remote Sensing in Yellowstone National Park, Wyoming: I. Forage Nutritional ValuesHyperspectral 1-m-resolution remote sensing has the potential to reduce the time spent sampling and reduce spatial sampling errors found in traditional forage nutritive analysis over large areas. The objective of this study was to investigate if 1-m-resolution hyperspectral techniques are useful tools to provide reliable estimates of forage nitrogen (N), phosphorus (P) and neutral detergent fiber (NDF) in Yellowstone National Park. The vegetative communities investigated varied in the amount of canopy coverage and species diversity, and ranged from xeric, semiarid environments to mesic, wetland/riparian environments. A large number of simple ratio-type vegetation indices (SRTVI) and normalized difference-type vegetation indices (NDTVI) were developed with the hyperspectral dataset. These indices were regressed against N, P, and NDF values from ground collections. We found that 1) there were strong linear relationships between selected SRTVI and N (R2 = 0.7), P (R2 = 0.65), and NDF (R2 = 0.87) nutritive values on an area basis (g m-2); and 2) there were no strong linear relationships (R2 < 0.3) between a variety of SRTVI and NDTVI and N, P, and NDF on a dry matter basis (g g-1 X 100). The lack of relationship is related to 1) the highly variable relationship between the dry matter biochemical signal and total plant biomass and water content and 2) the weakening of the biochemical signal from exposed soil in low-canopy situations, from nonphotosynthetic vegetation (bark, stems, and litter), and from different plant species.
Hyperspectral One-Meter-Resolution Remote Sensing in Yellowstone National Park, Wyoming: II. BiomassThis 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.