FLOOD DAMAGE ASSESSMENT IN A GIS – CASE STUDY FOR ANNOTTO BAY, JAMAICA
Price
Free (open access)
Volume
Volume 6 (2016), Issue 3
Pages
9
Page Range
508 - 517
Paper DOI
10.2495/SAFE-V6-N3-508-517
Copyright
WIT Press
Author(s)
H. GLAS, S. VAN ACKERE, G. DERUYTER & P. DE MAEYER
Abstract
Natural hazards do not only affect millions of people, but also cause material damages up to 300 billion USD per year worldwide. The SIDS (Small Island Developing States) are characterized by an extremely high vulnerability to these hazards, due to their low-lying, densely populated cities and their fragile economy. To limit the consequences of these hazards, technocratic interventions do not suffice. Therefore, new approaches that focus on flood risk management are developed. In this context, Annotto Bay, Jamaica, was chosen as a case study area to perform a flood damage assessment. In this study, a flood damage map was created for the 2001 flood caused by Tropical Storm Michelle. This map focuses on three types of damage: building, road and crop damage. The first type was calculated using the exact GPS locations of the buildings, as well as average replacement values for each building type and flood damage functions. The total building damage was then combined per land-use polygon to have an orderly visual view of the damage spread. Furthermore, the road damage was calculated, based on a road network extracted from satellite imagery. In a next step, as buildings are mostly located in proximity of roads, buffers were created around the road network, resulting in a more accurate visual view of the building damage spread. Then the crop damage was calculated based on maximum damage values for banana plantains and other crops, combined with the crop damage functions. The final result is a total damage map, visualizing the location of high risk areas with a high accuracy. Additionally, the total calculated damage was compared to the actual damage caused by the 2001 flood. This comparison shows promising results.
Keywords
damage map, flooding analysis, natural hazards, risk assessment