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[1] Coral reefs and associated benthic habitats are heterogeneous in nature. A remote sensor designed to discriminate these environments requires a high number of narrow, properly placed bands which are not currently available in existing satellite sensors. Optical hyperspectral sensors mounted on aerial platforms seem to be appropriate for overcoming the lack of both high spectral and spatial resolution of satellite sensors. This research presents results of an innovative coral reef application by such a sensor. Using hyperspectral Airborne Imaging Spectroradiometer for Applications (AISA) Eagle data, the approach presented solves the confounding influence of water column attenuation on substrate reflectance on a per-pixel basis. The hyperspectral imagery was used in band ratio algorithms to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). The water column correction technique produced a bottom albedo image which revealed that the dark regions comprised of sea grasses and benthic algae had albedo values %15%, whereas sand-and coral-dominated areas had albedos >30% and %15-35%, respectively. The retrieved bottom albedo image was then used to classify the benthos, generating a detailed map of benthic habitats, followed by accuracy assessment.

Abstract-Natural resource managers clamor for detailed reef habitat maps for monitoring smaller scale disturbances in reef communities. Coastal ocean color remote sensing techniques permit benthic habitats to be explored with higher resolution than ever before. The objective of this research was to develop an accurate benthic habitat map for an area off the northwest coast of Roatan Island, Honduras, using high-resolution multispectral IKONOS data. Atmospheric (Rayleigh and aerosol path radiance) and water column corrections (water depth and water column attenuation) were applied to the imagery, making it a robust method for mapping benthic habitats. Water depth for each pixel was calculated based on a site-specific polynomial model. A mechanistic radiative transfer approach was developed that removed the confound effect of the water column (absorption and scattering) from the imagery to retrieve an estimate of the bottom reflectance (albedo). Albedos were 12% for seagrass benthos, 12% to 24% for coral areas, and 24% for sand-dominated areas. The retrieved bottom albedos were then used to classify the benthos, generating a detailed map of benthic habitats, followed by accuracy assessment.

Research is presented that statistically analyzes the relationship between lake area and precipitation. These hydrologic variables are assessed in part using LANDSAT MSS satellite data and digital‐image processing techniques. Results show dramatic regional hydrologic differences in lake area fluctuations and in lake area response to short term climatic variation.