Abstract
Geographical mapping of disaster risk is an important task in disaster planning and preparedness. Heterogeneous data from various sources are integrated to identify regions having high probability of disasters. The nature of data and work-flow for risk assessment are however varying in nature in each scenario. In this work we propose a service oriented architecture to automate the process of disaster mapping. Open Geospatial Consortium Standards are implemented for this purpose. The framework can aid automated risk assessment under complex multi-modal disasters over large scale geospatial locations by integrating heterogeneous data sources. A Case study is presented for flood risk assessment for a coastal region in West Bengal, in Eastern India.
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Chakraborty, O., Das, J., Dasgupta, A., Mitra, P., & Ghosh, S. K. (2016). A geospatial service oriented framework for disaster risk zone identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9788, pp. 44–56). Springer Verlag. https://doi.org/10.1007/978-3-319-42111-7_5
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