Progress on the CAO Hyperspectral / LIDAR Imagery Project

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    Progress on the CAO Hyperspectral / LIDAR Imagery Project - Presentation Transcript

    1. Very High-resolution Imagery for Remote Sensing in Hawai`i Stephen Ambagis1 Jim Jacobi2 1Hawai`i Cooperative Studies Unit, UH Hilo 2U.S. Geological Survey
    2. What happens in a vacuum • Presently there are no local commercial aerial digital imagery providers • Two systems are breaking onto the scene • Both are focused on research and conservation • No overlap in base products, complimentary systems • Both systems are producing new products This presents the user community with a very unique situation, one that could progress Hawaii’s conservation goals more than ever imagined
    3. Carnegie Airborne Observatory – Hyperspectral imagery, 350 bands, 30 cm – Full waveform LIDAR Contact: Greg Asner email gpa@stanford.edu website- http://cao.stanford.edu/
    4. Resource Mapping – Very high resolution multispecral, 4 bands, 20 cm resolution – Ultra high resolution natural color, 3 bands, 1 cm resolution Contact: Dana Slaymaker Email info@resourcemappinggis.com Web site http://resourcemappinggis.com/
    5. Resource Mapping plane CAO plane and system and system
    6. • Fist contracted through USGS to do pilot research for TNC, Army, and Fish & Wildlife lands. • USGS funded development of next generation system that included image normalization for direct comparison and dual scale system • Initial results were promising • Recently TNCH has taken a leading role in implementation creating Resource Mapping Hawaii, local capacity
    7. Matching multispectral and natural color imagery over the Hakalau National Wildlife Reserve This dual-scale approach is especially helpful with species like Australian tree fern which is not distinguishable from the native fern species using any spectral identifiers. Resource Mappings goal is usually to find the lowest resolution adequate to a specific mapping need to reduce costs, but the dual camera set up gives them several options to meet these needs.
    8. A subsection of the natural color with it’s corresponding multispectral. The multispectral shows better spectral discrimination between trees while the natural color has more detail. A three times increase in spatial resolution in the natural color was sufficient to distinguish the tree species needed to map in the the Hakalau National Wildlife Reserve.
    9. Example of Ultra High Resolution Image Interpretability Psidum cattelianum Pandanus Psidum tectorius cattelianum Melastoma candidum Schefflera actinophylla Metrosideros polymorpha Macaranga mappa Cecropia obtusifolia Nephrolepis Melochia multiflora umbellata Trema orentalis 2 cm resolution
    10. Range of sub-sampling options, from 7 cm (above) to 1cm per pixel Detail of a single fern at both resolutions
    11. Current Status of Systems • Current product lines – Resource mapping products are focused on very fine detailed image interpretation over small to moderate AOI’s. – CAO data is geared toward large scale, automated, image analysis. • Availability – Resource Mapping will be local in June of this year with a dedicated plane, pilot, and processing facility – CAO is local but still in research phase of development from a large scale implementation perspective. • Cost – Resource Mapping produces full coverage, 2 scale, ortho-imagery at less than $2.00 per acre. – CAO costs requests should be directed to Greg Asner of Carnegie.
    12. Summary • Carnegie Airborne Observatory – Huge potential for automated large scale mapping of certain species, vegetation structure, and physiology; high-resolution DEMs. – True costs still being determined; currently available with conditions; long term availability being determined. • Resource Mapping – Straight forward approach to mapping and monitoring plant communities and species using image interpretation with ultra high resolution data – Known costs, fast and simple tasking ability.
    13. Carnegie Airborne Resource Mapping Observatory – Very high resolution – Hyperspectral multispecral, 4 bands, imagery, 350 bands, 20 cm resolution 30 cm resolution – Ultra high resolution – Full waveform natural color, 3 bands, LIDAR 1 cm resolution Contact: Greg Asner Contact: Dana Slaymaker email gpa@stanford.edu Email info@resourcemappinggis.com website- http://cao.stanford.edu/ Web site http://resourcemappinggis.com/ Note: Any use of trade, product, or firm names in this presentation is for descriptive purposes only and does not imply endorsement be the U.S. Government.

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    Data Discovery Day
    03/06/2008
    Jim Jacobi
    USGS
    Biolo more

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