Climate change and disaster impact reduction

Based on papers presented at the 'UK - South Asia Young Scientists and Practitioners Seminar on Climate Change and Disaster Impact Reduction' held at Kathmandu, Nepal on 5-6 June, 2008

Mutual alliances for local disaster risk reduction, response and resilience planning: a case study from Kathmandu

This project provided a central focus for the improvement of the local emergency responses of Kathmandu Metropolitan City Fire Brigade. In particular, donated fire fighting equipment and training increased the efficiency and effectiveness of the Kathmandu Metropolitan City based fire fighters. The project helped fire-fighters to acquire skills that would prepare them to fight disasters and increase adaption to new and emerging risk in the city. This initiative was unique in that it was the first situation to arise wherein serving fire fighters from Tyne and Wear and Northumberland Fire and Rescue Services with researchers form Northumbria University came together with their colleagues from a developing nation to share skills, ideas and fire-fighting tactics and techniques in a forum characterised by openness and the spirit of sharing. This initiative also benefited to the UK fire fighters and researchers in that they will benefit from sharing the knowledge and techniques used by the Kathmandu fire fighters in the absence of technologically advanced equipment and vehicles

An adaptation of a macroscale methodology to assess the direct economic losses caused by Tropical Cyclone Idai in Zimbabwe

Tropical cyclones are among the costliest disasters in the world, with reported losses amounting to billions of US dollars on an annual basis. To reduce the impact of disasters including cyclones, Zimbabwe signed the Sendai Framework whose Target C is aimed at reducing the direct economic losses of disasters. Under the direction of the United Nations Office for Disaster Risk Reduction (UNDRR), an open-ended intergovernmental expert working group (OIEWG) developed a simple methodology for estimating direct disaster-economic loss. Therefore, this study tested the applicability of the OIEWG methodology in assessing the direct economic losses induced by Tropical Cyclone Idai (TCI) in Zimbabwe. The results revealed that TCI inflicted huge losses in most sectors of the economy, notably the housing, agriculture and the critical infrastructure. The sectoral analysis approach of the OIEWG methodology worked well in distinguishing direct and indirect loses as well as in underlining the need to adopt and effectively implement adequate risk reduction strategies in the built environment. Strengthening such strategies such as the ‘build back better’ principle, cyclone forecasting and warning systems and constructing cyclone-resilient infrastructure is critical in order to minimise direct losses attributed to cyclones

Semi-automatic classification for rapid delineation of the geohazard-prone areas using Sentinel-2 satellite imagery

The study of land use land cover has become increasingly significant with the availability of remote sensing data. The main objective of this study is to delineate geohazard-prone areas using semi-automatic classification technique and Sentinel-2 satellite imagery in Bhutan. An open-source, semi-automatic classification plugin tools in QGIS software enabled efficient and rapid conduct of land cover classification. Band sets 2-8, 8A, and 11-12 are utilized and the virtual colour composites have been used for the clustering and creation of training samples or regions of interest. An iterative self-organizing data analysis technique is used for clustering and the image is classified by a minimum distance algorithm in the unsupervised classification. The Random Forest (RF) classifier is used for the supervised classification. The unsupervised classification shows an overall accuracy of 85.47% (Kappa coefficient = 0.71) and the RF classifier resulted in an accuracy of 92.62% (Kappa coefficient = 0.86). A comparison of the classification shows a higher overall accuracy of the RF classifier with an improvement of 7.15%. The study highlights 35.59% (512,100 m2) of the study area under the geohazard-prone area. The study also overlaid the major landslide polygons to roughly validate the landslide hazards