Informatics for Equitable Recovery in Nepal
A collaboration between the Earth Observatory of Singapore, Stanford Urban Resilience Initiative, ETH Zurich, and Kathmandu Living Labs — funded by the World Bank Innovations Fund.
Drawing on data collected in the aftermath of the 2015 Gorkha earthquake in Nepal, this project combines data from multiple sources, including remote sensing proxies, field surveys and social scientific data, to better inform post-disaster aid allocation and recovery planning.
Novel methods for large-scale dynamic probabilistic risk modelling
Current probabilistic disaster risk assessment methods have been limited to static analyses (i.e. based on the current condition of hazard, vulnerability, and exposure) often leading to large underestimation of risk.
This work focuses on developing an urban/regional risk analysis framework that is intrinsically time-dependent. The framework utilises multi-level agent-based modeling to simulate complex and dynamic urban environments at multiple spatial and temporal scales.
Ecosystems Services for Flood Risk Reduction
In collaboration with the Natural Capital Project based in Stanford University, this project looks to quantify the flood regulating ecosystems services using the risk framework. The goal of this project is to allow better comparisons between nature-based solutions with standard engineering-based “grey infrastructures”.
This project is funded by the Singapore National Research Foundation (NRF) and an Environmental Ventures Project grant from Stanford University,
Evaluation of Natural Catastrophe Impact in Megacities
This research focuses on disaster loss assessment in megacities, especially through future projections. A cellular automata-based urban growth model us used for the prediction of expansion in built-up area of megacities to estimate the loss in macro-level.