Publicaties

Michellier, C.,  Wolff, E. & Kervyn, F. 2015. ‘Vulnerability and resilience to geological hazards: the approach developed in GeoRisCA project’. Colloque International “Résilience aux catastrophes naturelles d’origine anthropique en République démocratique du Congo”. Book of abstracts.

Conference abstract

The densely populated area extended from the North Kivu province in Democratic Republic of the Congo (DRC) to North Burundi and East Rwanda is vulnerable to several geohazards, such as landslides, intense seismicity, the very active Virunga volcanoes: Nyiragongo and Nyamulagira. In that perspective, pregnant questions are: how vulnerable is the population? How to assess their vulnerability? Do they have resilience mechanisms to face such potential disaster? How do they consider risk in their daily life? What are the role of the local institutions to tackle the vulnerability and to enhance the resilience of the people and assets? For the first time in this region, a scientific research aims at (1) assessing the geological leading processes responsible for these hazards, (2) depicting the vulnerability based on the analysis of the local institutions’ prevention and preparedness activities, as well as on statistical data collected at the household’s level, and (3) understanding risk perception and resilience mechanisms identified through anthropological qualitative survey, conducted at an individual scale. In the framework of the GeoRisCA project, this paper presents and discusses the methodology developed to address the above questions. In the context of Bukavu and Goma cities, it has required a specific methodology combining space-born and ground-based techniques. Satellite imagery analysis has allowed estimating the population and mapping its distribution; in parallel, household surveys has enabled to calibrate these remote sensing data and to characterize the studied population. The preliminary results demonstrate that this approach is reliable, rapid and easy-to-repeat, providing decision makers with essential data.