Classifying benthic habitats and deriving bathymetry at the Caribbean Netherlands using multispectral Imagery. Case study of St. Eustatius

Benthic habitats (habitats occurring at the bottom of a water body) and coral reef ecosystems provide many functions. Currently, however, worldwide coral reefs are threatened by a number of factors and are degrading rapidly. Benthic maps are important for management, research and planning, but the benthic communities around St. Eustatius have not yet been accurately mapped or described. Remote sensing imagery has been found to be a useful tool in providing timely and up-to-date information for benthic mapping and offers an approach that may complement the limitations 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, corrections for sun-glint effect and water column attenuation 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 sun-glint removal method improved the total accuracy of the benthic habitat mapping by 3.4% for QuickBird and by 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 usefulness of the classification results of this study is still limited since almost 50% was wrongly classified, however, including additional variables (e.g. depth or exposure) in the classification algorithm may substantially increase classification success. This should be explored in follow-up research. The effectiveness of the ratio method to calculate the bathymetry using multispectral imagery has been confirmed. Results can be useful, especially if no other bathymetric data are available. The coefficients of determination (r) 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. We show that the ratio method works better for shallow areas, with a root mean square error of 2.32 m and 2.47 m, respectively. Biologically a depth difference of 2.5m, especially in shallow areas, can however make a large difference in the composition of the benthic community. Results also indicate that the accuracy of the ratio method is sensitive to bottom type (e.g. sand gives the highest accuracy). Overall, better bathymetric values were obtained with QuickBird than with WorldView-2. Additional adjustments of the model, better ground-truthing data, and better satellite images may increase the accuracy of the estimates. This research indicates how remote sensing can assist coral reef status and ecology assessments over large areas. At present the applicability is limited to only the coarsest habitat types, but further improvements in the classification are possible and should be explored. IMARES rapport C143/13; Alterra rapport 2467 3 of 96