Imaging derivative spectroscopy for vegetation dysfunction assessments

摘要

The practical application of current airborne and future satellite or space station based high spectral resolution (hyperspectral) imagery to vegetative canopies (sparse or dense) and resulting derived bio-physical variables will depend upon our ability to rapidly apply scientifically based algorithms. Key to these rapid assessments is the selection of the best or optimal channels or bands for detection of plant stress or dysfunction. Previous work has demonstrated the potential of utilizing high spectral resolution optical signatures for detecting plant stress related to the vegetation's moisture within the leaf structure. Future algorithms and techniques need to discriminate plant species as well as any plant dysfunction or stresses in terms ofleaf chemistry or other canopy bio-physical variables in order to improve operational advances in the use of hyperspectral imagery for environmental surveillance, agriculture and earth system science management. Second derivative imagery based upon derivative algorithms and selected bands are presented for AVIRIS imagery of Kennedy Space Center, Cape Canaveral and the Satellite Beach region of central Florida. The algorithms show potential for being used as the basis for firmware or "silicon strategy" based algorithms in the future.