Hyperspectral remote sensing of coral reefs: Deriving bathymetry, aquatic optical properties and a benthic spectral unmixing classification using AVIRIS data in the Hawaiian Islands

My research focuses on the development and application of hyperspectral remote sensing as a valuable component in the assessment and management of coral ecosystems. Remote sensing provides an important quantitative ability to investigate the spatial dynamics of coral health and evaluate the impacts of local, regional and global change on this important natural resource. Furthermore, advances in detector capabilities and analysis methods, particularly with respect to hyperspectral remote sensing, are also increasing the accuracy and level of effectiveness of the resulting data products. Using imagery of Kaneohe Bay and French Frigate Shoals in the Hawaiian Islands, acquired in 2000 by NASA's Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), I developed, applied and evaluated algorithms for analyzing coral reefs using hyperspectral remote sensing data. Research included developing methods for acquiring in situ underwater reflectance, collecting spectral measurements of the dominant bottom components in Kaneohe Bay, applying atmospheric correction and sunglint removal algorithms, employing a semianalytical optimization model to derive bathymetry and aquatic optical properties, and developing a linear unmixing approach for deriving bottom composition. Additionally, algorithm development focused on using fundamental scientific principles to facilitate the portability of methods to diverse geographic locations and across variable environmental conditions. Assessments of this methodology compared favorably with available field measurements and habitat information, and the overall analysis demonstrated the capacity to derive information on water properties, bathymetry and habitat composition. Thus, results illustrated a successful approach for extracting environmental information and habitat composition from a coral reef environment using hyperspectral remote sensing.