Application of Hybrid Techniques (Self-Organizing Map and Fuzzy Algorithm) Using Backscatter Data for Segmentation and Fine-Scale Roughness Characterization of Seepage-Related Seafloor Along the Western Continental Margin of India

In this paper, a seafloor characterization technique to unravel the number of data classes using multibeam echo-sounding backscatter data has been demonstrated. An application of self-organizing maps (SOMs) to backscatter profile data has been developed to determine the number of classes. Consequently, the fuzzy C-means (FCM) method is employed thereafter, using the number of class information of the backscatter profiles segmentation. The use of the soft-computational technique for seafloor backscatter data facilitates in achieving stationary profile data sets suitable for seafloor roughness model application. The power spectral density (PSD) function of the segmented profiles provides the power law parameters (beta and alpha') through curve fitting, using power law expression. The data acquired from western continental margin of India (WCMI), off Goa, reveal five distinct classes of backscatter strength having different segment lengths. The estimated roughness parameters (beta and alpha') of the segmented profiles provide quantitative information about the area seafloor roughness. A gridded map of the estimated roughness parameter is (beta) generated using the "krigging" method. The gridded map and the class of the segmented profiles overlaid on the backscatter map have been presented, which is a first time application relevant for the understanding of the seafloor. The present study underscores a combination of soft-computational (SOM and FCM) and numerical techniques (power spectral density at short and fine scales) to effectively recognize the seafloor processes and the associated sedimentological dynamics in a complex geographical environment (including the pockmarks and faulted structures), which is subjected to strong bottom currents and seasonal upwelling

Threats to environmentally sensitive areas from peri-urban expansion in Mauritius

There are 60 inhabited tropical island countries covering c. 3.54 million km2 of land. Tropical islands are disproportionately rich in endemic plants, birds, molluscs, and other invertebrates (Whittaker and Fernandez-Palacios 2007) relative to similar mainland habitats (see, for example, Kier et al. 2009). The majority of global coral and seagrass diversity is located in the reefs, shoals, and lagoons of tropical islands (Spalding et al. 2001, 1997), the islands accounting for 2.4% of the global land area, but housing a much greater swathe of the Earth's biological uniqueness (Kreft et al. 2008). At the same time, the topography of most tropical islands is relatively steep, compressing their high terrestrial and coastal marine biological value into relatively small areas. This compression also reduces the average size of watersheds and shortens river main stems, in particular relative to the hydrological space of continental systems (Milliman et al. 1999). Consequently, island nations rely heavily on groundwater extraction and river impoundments to provide clean water to urban areas, particularly during periods of low rainfall