Effective and innovative Big Data processing and analysis is becoming increasingly important for risk assessment in data-scarce locations, particularly when defining and scaling up the present human and economic value of assets and when characterizing the natural hazards to which they may be exposed. This is driven primarily by dramatic increases in the volume and spatial/temporal resolution of remotely-sensed datasets and by social media sourced derivatives. Here, we present a few examples from Uttarakhand.
In January 2019, with financial support from the World Bank, the Uttarakhand State Government engaged a team of experts from DHI Water & Environment (S) Pte. Ltd, the Asian Institute of Technology (AIT) and the Evaluación de Riesgos Naturales (ERN), to complete a disaster risk assessment of the entire state and quantify, for the first time, the threat from natural hazards and the exposure of communities and critical infrastructure.
It was found that buildings are one of the major elements-at-risk. To overcome a gap of accurate information on the location of buildings, all building clusters and individual (distinctly standalone) buildings, in Uttarakhand, were digitized from high-resolution satellite images covering the whole state (an area of 53,483 km2). Considering the large number of buildings in Uttarakhand, the whole state was divided into 60,000 grids that were each randomly assigned to a data entry operator for digitizing using an application. Figure 1 depicts the workflow of the tool, developed for rapid and collaborative efforts, that captures the building clusters for the entire state.
Additional details and more practices like this can be found in Geospatial Practices for Sustainable Development in Asia and the Pacific 2020: A Compendium