[1] Euphotic zone depth, z 1% , reflects the depth where photosynthetic available radiation (PAR) is 1% of its surface value. The value of z 1% is a measure of water clarity, which is an important parameter regarding ecosystems. Based on the Case-1 water assumption, z 1% can be estimated empirically from the remotely derived concentration of chlorophyll-a ([Chl]), commonly retrieved by employing band ratios of remote sensing reflectance (R rs ). Recently, a model based on water's inherent optical properties (IOPs) has been developed to describe the vertical attenuation of visible solar radiation. Since IOPs can be nearanalytically calculated from R rs , so too can z 1% . In this study, for measurements made over three different regions and at different seasons (z 1% were in a range of 4.3-82.0 m with [Chl] ranging from 0.07 to 49.4 mg/m 3 ), z 1% calculated from R rs was compared with z 1% from in situ measured PAR profiles. It is found that the z 1% values calculated via R rs -derived IOPs are, on average, within $14% of the measured values, and similar results were obtained for depths of 10% and 50% of surface PAR. In comparison, however, the error was $33% when z 1% is calculated via R rs -derived [Chl]. Further, the importance of deriving euphotic zone depth from satellite ocean-color remote sensing is discussed.

New coastal ocean remote sensing techniques permit benthic habitats to be explored with higher resolution than ever before. A mechanistic radiative transfer approach is developed that first removes the distorting influence of the water column on the remotely sensed signal to retrieve an estimate of the reflectance at the seafloor. The retrieved bottom reflectance is then used to classify the benthos. This spectrally based approach is advantageous because model components are separate and can be evaluated and modified individually for different environments. Here, we applied our approach to quantitatively estimate shallow-water bathymetry and leaf area index (LAI) of the seagrass Thalassia testudinum for a study site near Lee Stocking Island, Bahamas. Two high-resolution images were obtained from the ocean portable hyperspectral imager for low-light spectroscopy (Ocean PHILLS) over the study site in May 1999 and 2000. A combination of in situ observations of seafloor reflectance and radiative transfer modeling was used to develop and test our algorithm. Bathymetry was mapped to meter-scale resolution using a site-specific relationship (r 2 ϭ 0.97) derived from spectral ratios of remote sensing reflectance at 555 and 670 nm. Depth-independent bottom reflectance was retrieved from remote sensing reflectance using bathymetry and tables of modeled water column attenuation coefficients. The magnitude of retrieved bottom reflectance was highly correlated to seagrass LAI measured from diver surveys at seven stations within the image (r 2 ϭ 0.88-0.98). Mapped turtlegrass LAI was remarkably stable over a 2-yr period at our study site, even though Hurricane Floyd swept over the study site in September 1999.Managing and preserving coastal marine resources is a formidable challenge given the rapid pace of change affecting coastal environments. Fast, accurate, and quantitative tools are needed for detecting change in coastal ecosystems. Traditional in situ surveys are time and labor intensive, generally lack the spatial resolution and precision required to detect subtle changes before they become catastrophic, and can be difficult to maintain from year to year (Orth and Moore 1983;Peterson and Fourqurean 2001). Aerial photography provides more effective spatial coverage and has been used to semiquantitatively map benthic substrates (Ferguson et al. 1993;Kirkman 1996;Sheppard et al. 1995), but it is not effective at distinguishing color differences due to variations in water depth. The spectral reflectance obtained from digital remote sensing imagery represents a considerable advancement over conventional photography and allows AcknowledgmentsWe acknowledge the helpful comments from our anonymous reviewers and all of the many individuals who aided in collection of the in situ oceanographic field data (including S. Wittlinger, S. Palacios, M. Cummings). We also acknowledge J. Bowles, M. Kappus, and M. Carney for collecting the PHILLS data. Acknowledgements are extended to E. Boss and R. Zaneveld for supplying the IOPs, ...

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance ͑R rs ͒ spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured R rs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.

[1] The propagation of downwelling irradiance at wavelength l from surface to a depth (z) in the ocean is governed by the diffuse attenuation coefficient, K d (l). There are two standard methods for the derivation of K d (l) in remote sensing, which both are based on empirical relationships involving the blue-to-green ratio of ocean color. Recently, a semianalytical method to derive K d (l) from reflectance has also been developed. In this study, using K d (490) and K d (443) as examples, we compare the K d (l) values derived from the three methods using data collected in three different regions that cover oceanic and coastal waters, with K d (490) ranging from $0.04 to 4.0 m À1 . The derived values are compared with the data calculated from in situ measurements of the vertical profiles of downwelling irradiance. The comparisons show that the two standard methods produced satisfactory estimates of K d (l) in oceanic waters where attenuation is relatively low but resulted in significant errors in coastal waters. The newly developed semianalytical method appears to have no such limitation as it performed well for both oceanic and coastal waters. For all data in this study the average of absolute percentage difference between the in situ measured and the semianalytically derived K d is $14% for l = 490 nm and $11% for l = 443 nm.

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