Spatial planning is considered to be an important instrument in disaster risk management, by which human exposure and vulnerability could be reduced and thereby disaster losses. And in order to make informed planning decisions, adequate and reliable hazard and risk information is indispensable. Therefore, in the first part of this study, the use of hazard and risk information in the physical planning process of 5 Caribbean countries (Grenada, Saint Vincent, St. Lucia, Dominica, and Belize) was examined through literature review and direct interviews with senior staff of each physical planning unit. Furthermore, fragility and resilience indices were produced for Grenada to analyze its vulnerability to natural hazards. These indices were constructed by adopting an indicator based approach making use of publicly available census data from 2011 that was aggregated at the enumeration district level. The main selected indicators are age, gender, insurance, education, housing, livelihood, health etc. The Spatial Multi Criteria Evaluation module of ILWIS was used to combine different factor maps and produce indices. Since, purely census data was used for measuring vulnerability these indices provide in a way household level fragility and resilience in the country. To check the sensitivity of the model and indices, both percent and absolute values of indicators were tested. A concept of a flood hazard matrix is introduced for Grenada that is based on probability of flood occurrence and its intensity (height). Flood hazard maps produced by ITC using OpenLISEM are classified taking this hazard matrix and the resultant maps could now be utilized for physical planning decisions. Unfortunately the census data is not geo-located, which makes it difficult to use in an exposure analysis. Therefore, a test was made to geo-locate census data in selected sites. Additionally, a country-wide population distribution map at building level was produced for the main Island following a dasymetric mapping concept by utilizing census data and available building footprints, which were visually classified according to their occupancy types. Using GIS spatial overlay techniques exposure analysis was carried to identify number of buildings and estimated population that is exposed to flooding and landslides.