Submitted to: Geospatial Information in Agriculture and Forestry International Conference
Publication Type: Proceedings
Publication Acceptance Date: November 5, 2005
Publication Date: N/A
Interpretive Summary: Hyperspectral sensors are used to obtain a detailed reflectance spectrum of the land surface. The AVIRIS sensor (Airborne Visible Infrared Imaging Spectrometer) is one of NASA's best hyperspectral sensor. Image data were acquired on two dates covering a long-term grazing experiment at the Agricultural Research Service's Central Plains Experimental Range near Nunn, Colorado. Biomass and leaf area index (LAI) were very different among the grazing treatments, but vegetation cover were similar. The AVIRIS data could not be used to detect the differences in biomass or leaf area index, indicating the sensor was primarily seeing vegetation cover. These results were supported by canopy reflectance models.
Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data were acquired on two dates (25 July 1995 and 6 August 1998) over the Agricultural Research Service's Central Plains Experimental Range (CPER) near Nunn, Colorado. AVIRIS data were first corrected to reflectances using the ATREM model, then were further corrected using an empirical line with field reflectance data. For a long-term grazing intensity experiment (light, medium, heavy), normalized difference vegetation indices (NDVI) were equal among treatments for both years. There was no relationship between NDVI and biomass or leaf area index (LAI), even though the LAI's were less then two. Endmember mixture analyses showed the green cover fraction was equal to the measured cover and the shadow cover fraction was equal to the shrub cover. Application of mixture models to reflectances of stacked leaves confirm that NDVI is primarily responsive to differences in green cover and secondarily responsive to LAI.