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This thesis presents a new template for multidisciplinary habitat mapping that combines the analyses of seafloor geomorphology, oceanographic proxies and modelling of associated biologic features. High resolution swath bathymetry of the Faial and western Pico shelves is used to present the first state-of-the-art geomorphologic assessment of submerged island shelves in the Azores. Solid seafloor structures are described in previously unreported detail together with associated volcanic, tectonic and erosion processes. The large sedimentary expanses identified in the area are also investigated and the large bedforms identified are discussed in view of new data on the local hydrodynamic conditions. Coarse-sediment zones of types hitherto unreported for volcanic island shelves are described using swath data and in situ imagery together with sub-bottom profiles and grainsize information. The hydrodynamic and geological processes producing these features are discussed. New oceanographic information extracted from satellite imagery is presented including yearly and seasonal sea surface temperature and chlorophyll-a concentration fields. These are used as proxies to understand the spatio-temporal variability of water temperature and primary productivity in the immediate island vicinity. The patterns observed are discussed, including onshore-offshore gradients and the prevalence of colder/more productive waters in the Faial-Pico passage and shelf areas in general. Furthermore, oceanographic proxies for swell exposure and tidal currents are derived from GIS analyses and shallow-water hydrographic modelling. Finally, environmental variables that potentially regulate the distribution of benthic organisms (seafloor nature, depth, slope, sea surface temperature, chlorophyll-a concentration, swell exposure and maximum tidal currents) are brought together and used to develop innovative statistical models of the distribution of six macroalgae taxa dominant in the infralittoral (articulated Corallinaceae, Codium elisabethae, Dictyota spp., Halopteris filicina, Padina pavonica and Zonaria tournefortii). Predictive distributions of these macroalgae are spatialized around Faial island using ordered logistic regression equations and raster fields of the explanatory variables found to be statistically significant. This new approach represents a potentially highly significant step forward in modelling benthic communities not only in the Azores but also in other oceanic island shelves where the management of benthic species and biotopes is critical to preserve ecosystem health.