Natural Hazard Monitoring: a early warning method to delineate potentially affected areas by Hurricane using a GIS model.

This research integrates the concept that the subject of natural hazards and the use of existing remote sensing system in the different phases of a disaster management for a specific hurricane hazard, is based on the applicability of GIS model for increasing preparedness and providing early warning. The modelling of an hurricane event in potentially affected areas by GIS has recently become a major topic of research. In this context the disastrous effects of hurricanes on coastal communities and surroundings areas are well known, but there is a need to better understand the causes and the hazards contributions of the different events related to an hurricane, like storm surge, flooding and high winds. This blend formed the basis of a semi-quantitative and promising approach in order to model the spatial distribution of the final hazard alon! g the affected areas. The applied model determines a sudden onset zoning from a set of available parameters that include topography, bathymetry, storm track into coast proximity and river network. For all these parameters, key attributes based on SRTM and bathymetry data, are the river network delineation (based on the Strahler methodology) the slope data and coastline bathymetry identification. Complementary data for the final model includes remote sensed density rain dataset, elevation datasets for selected coastal drainage basins, and existing hurricane tracks inventories together with hurricane structure model (different buffers related to wind speed hurricane parameters in a GIS environment). To assess the overall susceptibility, the hazard results were overlaid with population dataset and landcover. The approach, which made use of a number of available global data sets, was then validated on a regional basis using past experience on hurricane frequency study over! an area that covers both developed and developing countries in the Ca ribbean region. As a final result we can state that remote sensing data analysed together with meteorological and environmental data in an integrated GIS system give a spatially resolved picture of the surface conditions and, in our context, information on the occurrence, extent and severity of hurricane hazard. The applied GIS model has then given rise to a long-lead system that can be set-up to allow such a early warning to go ahead.