Abstract:
Community resilience assessments and minimizing the anticipated disruptions to vulnerable communities, is a broad topic in disaster studies. In common practice, most of the indicator-based resilience assessment studies rely on statistical aggregation methods of tabular data collected for macro administrative units, as it is readily available in most of the countries. However, this method confronts severe drawbacks in converting such data into micro-scale geospatial units. To address those issues, this study proposes to utilize the Dasymetric Mapping Technique in the geospatial population resilience assessments, as it is capable of identifying the micro level impact to the population distribution as a pixel representation. In order to geospatially demonstrate the population exposure, the study has selected three major flooding events occurred in Colombo, Sri Lanka. The results revealed a great applicability of the proposed method as a statistical approach which estimates the exposed population by over 90% accuracy. Therefore, the proposed method is recommended to be utilized as an efficient tool of community resilience assessment as it is highly accurate in downscaling the spatial distribution of population data.
