Publications scientifiques
Franck Eitel Kemgang Ghomsi
Autres affiliations : University of Pisa · Université de Dschang · University of Maroua
Zakari Arétouyap* (Auteur correspondant)
Janvier Domra Kana
Nicola Perilli
Sandra Céleste Tchato
Research Square
Abstract The Cameroon Business City (CBC), Douala, is the Cameroon’s city which has the highest urbanisation and demographic growth rate. It is located on the Atlantic banks. Its geographic features are major indicators of various potential disasters, with natural (geological, hydrological, oceanographic, meteorological, biological) and/or anthropogenic (mainly industrial) drivers to be adequately managed. Disaster management is a tedious and complex process involving an important number of criteria to be considered and assessed. It includes a wide range of tasks such as forecasting, monitoring, evacuation, relief, search and rescue, rehabilitation and reconstruction, that can be grouped into three phases: pre-disaster, during disaster and post-disaster operations. Rather than preparing disaster response, this paper investigates the risk reduction by analysing the vulnerability of the CBC to disasters. It is a matter of predicting disasters by safeguarding timely preparedness on concerned institutions, government agencies, non-government organisations (NGOs) and citizens. The objective of this paper is to combine geographic information system (GIS), remote sensing (RS) and analytical hierarchy process (AHP) for disaster prediction in the CBC. A set of maps (with key role in disaster assessment) are derived and processed from satellite data. In addition to other thematic maps dealing with ecological, environmental, biophysical, and socioeconomic features, the aforementioned maps are processed as layers in a GIS environment using AHP to demarcate and classify the CBC by level of landslide risk and a gathering zone in case of a tsunami. Policy perspectives are also formulated to the attention of the municipal authorities, NGOs, planners and civil engineers.
