Classifying benthic habitats and deriving bathymetry at the Caribbean Netherlands using multispectral Imagery

Benthic habitats (habitats occurring at the bottom of a water body) and coral reef ecosystems provide many functions. Currently, however, coral reefs are threatened by a number of factors and degrade rapidly. Benthic maps are important for management, research and planning. Coral communities in the Caribbean Dutch island of St. Eustatius are generally in a good condition, but the benthic communities around St. Eustatius have not been yet accurately mapped.
Remote sensing imagery has been found to be a very useful tool in providing timely and up-to-date information for benthic mapping and offers an effective approach to complement the limitation of field sampling. Remote sensing in water, however, presents challenges mainly due to the complex physical interactions of absorption and scattering between water and light. Shorter wavelengths (-450 nm) penetrate deepest into the water column and longer wavelengths (-500-750 nm) are more rapidly absorbed and scattered. Therefore, the potential extent of use of remote sense imagery in the oceans relies more on shorter wavelengths (blue band), which have inherently noisier signals due to atmospheric effects.
This research explores the utility of multispectral imagery to identify and classify marine benthic habitats in the Dutch Caribbean island of St Eustatius. These include the comparison of two sensors with different spatial and spectral resolution, QuickBird (2.4m, 4 bands) and WorldView-2 (2.0m, 8 bands) for mapping benthic habitats. The study first investigates the existing methodologies for benthic habitat classification. The benefits of atmospheric correction, sun glint effect correction and water column attenuation correction on the accuracy of classification maps are also assessed. Then, an object and pixel based supervised classifications for the characterization of sea grass, sand and coral are performed. This research also evaluates the possibility to extract water depth from multispectral satellite imagery by the use of a ratio transform method. Bathymetric data is important for water column correction, to improve the classification accuracy and for the study of the ecology of the habitats.
Results showed that the best results for pixel-based image classification in QuickBird and WoldView-2 imagery were obtained after deglinting the image, with accuracies of 49.3% and 51.9% respectively. The sunglint removal method improved the total accuracy of benthic habitat mapping, by increasing before and after deglinting 3.4% for QuickBird and 6.3% for WorldView-2. Object-based classification provided slightly better classification results, with a 53.7% accuracy for QuickBird and 56.9% accuracy for WorldView-2. Therefore, it can be concluded that an object-oriented approach to image classification shows potential for improving benthic mapping. The classification accuracy did not increase after compensation for water column effects.
The effectiveness of the ratio method to calculate the bathymetry using multispectral imagery has been confirmed. The coefficients of determination (r2) achieved are statistically significant, 0.66 for QuickBird, and 0.41 for WorldView-2 (BG ratio) for a linear relation. The root mean square errors are 4.02 m for QuickBird and 5.11 m for WorldView-2. It has been proved that this method works better for shallow areas, with a root mean square error of 2.32 m and 2.47 m, respectively. Results also indicate that the ratio method is sensitive to variable bottom type. Overall, better bathymetric values were obtained with QuickBird than with WorldView-2.
This research provides a baseline for future benthic habitat classification of the Dutch Caribbean islands using remote sensing. The results of this study are a good example of how remote sensing data can be a useful and cost effective method to map benthic habitats and calculate bathymetry.

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