Bathymetry and the spatial distribution of benthic cover in coastal waters are of key importance in managing and monitoring our coastal water environments. Currently very little of the Western Australian shallow coastal water habitats are mapped, and for those maps that do exist, the spatial resolution generally is poor and the information is dated. Aircraft and space-borne hyperspectral sensors have been shown to be useful in imaging substrate features in shallow coastal waters. This paper describes a method for quantitatively estimating both bathymetry and benthic cover in shallow waters from hyperspectral imagery. The method incorporates a shallow water reflectance model, which accounts for the water column absorption and backscattering, water depth and substrate reflectance. The model was tested against simulated reflectance data, demonstrating the models' ability to retrieve appropriate fractional coverage of sediment, sea grass and brown algae for depths ranging from 1 - 12 m. The model was applied to a HyMap image encompassing a portion of the Jurien Bay Marine Park off the coast of Western Australia. The retrieved benthic cover products were compared to underwater video observations sampled within the image. The comparison shows the method's great potential for characterizing key aspects of marine ecosystems from remotely sensed hyperspectral data.
Hyperspectral remote sensing provides a particularly useful means
of determining inherent optical properties of coastal waters where
constituents other than phytoplankton add to the optical
complexity of the water column. The substantial number of
channels, about 200 for most hyperspectral sensors, enables many
of the constituents within the water column to be identified
spectrally. Additionally, in shallow water the water leaving
radiance may include a signal reflected from the sea bottom. A
hyperspectral radiometer was deployed on monthly oceanographic
cruises off the coast near Perth, Western Australia, to make
observations. Field measured reflectance spectra were used as
input into a slightly modified version of a reflectance model
developed by Lee <i>et al</i>, 1999. Products, including the
concentrations of chlorophyll-<i>a </i>(Chl-<i>a</i>), coloured
dissolved organic matter (CDOM), and suspended sediments (SS), as
well as the water column depth (H), were extracted from the
reflectance model by incorporating an optimisation technique. A
Levenberg-Marquardt retrieval scheme was utilised in the
optimisation. This scheme involved minimizing the difference
between the modelled and measured spectral reflectance curves.
Water samples were also collected on the monthly oceanographic
cruises and used to determine the concentrations of
chlorophyll-<i>a</i>, CDOM and SS. Water depth was measured using
the boat's echo sounder. The model-derived products were compared
to <i>in situ </i>measurements. The mean difference between model
retrieved depth and <i>in situ </i>depth was 12.5 % or 1.4 m (<i>R</i><sup>2</sup> = 0.98, <i>N</i>=11). Excluding two field measurements taken in the Marmion Marine Park, the mean RMS difference in depth was 7.6 % or 0.9 m (<i>R</i><sup>2</sup> = 0.99, <i>N</i>=9). The mean RMS difference between retrieved Chl-<i>a</i> concentration and <i>in situ </i>measured Chl-<i>a </i>was 11.1 % or 0.044 mgm<sup>-3 </sup>(<i>R</i><sup>2</sup> = 0.91, <i>N</i>=8). These preliminary results suggest that the reflectance model works well for depth and Chl-<i>a</i> retrieval for Western Australian coastal waters and their sandy substrate.
Remote sensing algorithms for retrieving estimates of oceanic constituent concentrations, such as chlorophyll concentration, require as input measurements of spectral water-leaving radiance. This measurement is typically obtained from space-based sensors such as SeaWiFS or MODIS. Some polar orbiting sensors have tilt and scan capabilities such that sensor view angles can at times exceed 70 degrees from the zenith. Inherent in algorithms applied to such remotely sensed measurements are assumptions on how the off-nadir radiance varies in intensity compared to the total upwelling irradiance. Typical ocean reflectance equations incorporate two factors, <i>f</i> (in <i>R</i> = <i>f b<sub>b</sub>/a</i>) and <i>Q</i> (where <i>Q</i> = <i>E<sub>u</sub>/L<sub>u</sub></i>), which relate the water-leaving radiance in 3 dimensions to the incident (sky and sun) irradiance. A Monte Carlo ocean optical model was developed and used to investigate the three dimensional nature of water leaving radiance for typical open ocean optical conditions. Equations for predicting <i>f</i> were developed as well as a data base of <i>Q </i>factors for different solar and viewing geometries as functions of <i>b</i>, <i>b<sub>b</sub></i> and <i>a</i>. Results derived from the Monte Carlo model were then used here to develop a more in-depth study of <i>f </i>based on HYDROLIGHT. Improved equations for predicting f have been developed and are compared to predictions of <i>f </i>from HYDROLIGHT. Examples of how these improved estimates of <i>f</i> and <i>Q</i> may be applied to a chlorophyll concentration algorithm for open ocean waters will be presented.
1996 marks the revival of the production of visible channel imagery of the ocean with the planned launches of Japan's ADEOS Ocean Color Temperature Sensor (OCTS), SeaWiFS, and the EOS MODIS-N, with launch dates 1996, 1997 and 1998 respectively. At least three other missions are at various stages of planning. The missions will initiate a continuous global time series of ocean color data that should extend well into the next century. The classification of water types and application of pigment retrieval algorithms specific to those water types may increase the accuracy of retrieved pigment concentrations. The aim is to develop a pigment concentration retrieval algorithm tunes to local oceanic conditions. Investigation of the effects of the physical and optical properties of the ocean on the water- leaving radiance, and the development of an inversion scheme for measurement of those physical and optical properties may be achieved through modeling. This approach also aids the design of validation programs. A simple relationship has been fond for predicting the reflectance of the ocean for different optical properties. The applicability of this relationship to chlorophyll concentration retrieval is being investigated. A multiple channel reflectance inversions has been used to derive pigment concentrations from model results. Preliminary results show that the scheme is sensitive to uncertainty in optical properties of water constituents. The scheme does however provide some indication of the confidence limits applicable to the retrieved concentration.
Conference Committee Involvement (1)
Remote Sensing of Inland, Coastal, and Oceanic Waters