Research Overview

My research covers the broad field of probabilistic risk analysis (aka mathematics of disasters), disaster risk reduction, post-disaster assessment and recovery. Spanning the entire disaster cycle, my research combines methods from spatial statistics, risk/reliability analysis, statistical learning and systems sciences in order to better understand the potential impact of disaster on society, and develop tools to promote resilient cities. My research lies at the intersection of urban planning, engineering and statistics. My focus is on cities and urban regions as they represent extremes in terms of potential casualties and losses, and require more complex analyses due to their dynamics in terms of populations, infrastructure systems and networks.

My research is highly interdisciplinary and collaborative. Among these collaborators are the Stanford Urban Resilience Initiative, the World Bank, the Global Facility for Disaster Reduction and Recovery (GFDRR) Innovations Lab, Google, the Natural Capital Project, the Humanitarian OpenStreetMap Team, the United States Geological Survey (USGS), and others.

Interests

  • Urban Risk Modeling and Forecasting
  • Quantitative models of resilience
  • Disaster impacts beyond fatalities and financial losses
  • Remote-sensing and crowd-sensing for rapid post-disaster assessment
  • Communicating Risk, Visualizing Uncertainty
  • Resilient post-disaster recovery

Research Projects

  • Quantifying Disaster Resilience

    The study of community disaster resilience has so far focused on qualitative analysis, post-disaster surveys and definition of resilience indexes. These have provided valuable insights into community vulnerability and capacity, but these methods have limited ability to support urban planning or design of infrastructure to pro-actively promote resilience. My research attempts to develop rigorous design-oriented quantitative measures of resilience. Current methods in probabilistic risk analysis are extended to probabilistic recovery analysis.

    Related publications and projects:

    Stanford Urban Resilience Initiative – Resilience Framework Project (2016-2017)

    Burton, H., Deierlein, G., Lallemant, D., Singh, Y., Measuring the Impact of Enhanced Building Performance on the Seismic Resilience of a Residential Community. Earthquake Spectra, doi:10.1193/040916EQS057M.

    Burton, H. Deierlein, G., Lallemant, D., Lin, T. (2015). A Framework for Assessing Building Performance Limit states that Inform Community Seismic Resilience, Journal of Structural Engineering Special Issue: Resilience-based design of structures.

  • Modeling Trajectories of Risk

    The dramatic urban transformation of the past century has shifted the landscape of risk, with cities becoming the major source of global risk. Yet current risk assessment models fall short in characterizing the spatial and temporal dynamics of the urban environments in terms of rapidly changing local exposure and vulnerability, often leading to large underestimation of risk.

    Related publications:

    Lallemant, D., Burton, H., Ceferino, L., Bullock, Z., Kiremidjian, A. A Framework and Case Study for Earthquake Vulnerability Assessment Of Incrementally Expanding Buildings. Earthquake Spectra, 2017.

    Lallemant, D.: “Modeling the Future Disaster Risk of Cities to Envision Paths Towards their Future Resilience.” Thesis (Stanford University), 2015.

    Lallemant, D., Wong, S., Kiremidjian, A., “A Framework for Modeling Future Urban Disaster Risk,” Chapter in “Understanding Risk: The Evolution of Disaster Risk Assessment Since 2005,” World Bank and GFDRR Publication, 2014.

    Lallemant, D., Kiremidjian, A.,“A Framework and Case Study for Dynamic Urban Risk Assessment,” 10th National Conference on Earthquake Engineering, Anchorage, Alaska, 2014.

  • Rapid Post-Disaster Impact Assessment

    This research proposes new approaches for rapid post-disaster impact assessment. Methods from statistical learning and geostatistics are used to assess post-disaster damage and quantify uncertainties. We are further conducting extensive work on crowd-based analysis of remote-sensing data for rapid damage detection.

    Related Publications and Projects:

    Stanford Urban Resilience Initiative – RADCrowd Project (2016-2017)

    Lallemant, D., Soden, R., Rubinyi, S., Loos, S., Barns, K., Bhattacherjee, G. (2017) Post-disaster damage assessments as catalysts for recovery: A look at assessments conducted in the wake of the 2015 earthquake in Nepal. Earthquake Spectra. (accepted 2017)

    Lallemant, D., Kiremidjian, A. (2014) “A Beta Distribution Model for Characterizing Earthquake Damage State Distribution,” Earthquake Spectra.

    C. Corbane, K. Saito, L. Dell’Oro, E.Bjorgo, S. Gill, B. Piard, C. Huyck, T. Kemper, G. Lemoine, R. Spence, R. Shankar, O. Senegas, F. Ghesquiere, D. Lallemant, G. Evans, R. Gartley, J. Toro, S. Ghosh, W. D. Svekla, B. Adams, and R. Eguchi (2011). “A Comprehensive Analysis of Building Damage in the 12 January 2010 Mw7 Haiti Earthquake Using High-Resolution Satellite and Aerial Imagery”, Photogrammetric Engineering & Remote Sensing

    Lallemant, D., Kiremidjian, A. (2013). “Rapid Post-Earthquake Damage Estimation using Remote-Sensing and Field-Based Damage Data Integration,” Conference paper and presentation, 11th International Conference on Structural Safety & Reliability, June 16-20, 2013. Columbia University New York, NY.

    Lallemant, D. (2010). “Haiti – Uses of Information Technology Products for Disaster Response & Recovery”, Keynote Presentation, Annual Workshop – Information Products Laboratory for Emergency Response, Nov 12, 2010, Rochester Institute of Technology, Rochester, NY.

  • Modeling Fragility

    This research investigates and proposes new statistical procedures for developing fragility models. The project further looks at the quantification and propagation of uncertainty in the fragility model through to loss.

    Related Publications:

    Lallemant D., Kiremidjian A. and Burton H. (2015), Statistical procedures for developing earthquake damage fragility curves. Earthquake Engineering and Structural Dynamics. doi: 10.1002/eqe.2522.

    Noh H. Y., Lallemant D., and Kiremidjian A. S. (2014) Development of empirical and analytical fragility functions using kernel smoothing methods, Earthquake Engineering and Structural Dynamics. doi: 10.1002/eqe.2505.

    Noh H., Lallemant, D., Kiremidjian, A. (2013). Development of Empirical and Analytical Fragility Functions Using Gaussian Kernel Smoothing Methods. 11th International Conference on Structural Safety & Reliability (ICOSSAR 2013). June 16-20, 2013. Columbia University New York, NY.

    Noh. H., Kiremidjian, A. Lallemant, D., (2012). “Issues Related to the Development of Empirical Fragility Functions,” Global Earthquake Model (GEM) Report.

  • Novel Technologies for Disaster Risk Assessment

    Project in collaboration with Google, using google’s new Earth-Engine platform to conduct rapid high-resolution earthquake risk analysis at urban and regional scales.

  • Post-Disaster Recovery

    Disasters make obvious the need to reduce risk in reconstruction, so that avoidable calamities are not repeated. Often, however, the demand and need for risk reduction in reconstruction is faced with significant obstacles due to the complexity and constant urgency of post-disaster environments. This research and work investigates some of the fundamental components for risk reduction in the post-earthquake recovery and reconstruction. It originates from extended work following the 2010 earthquake in Haiti, the 2011 earthquake in New Zealand and the 2015 earthquake in Nepal.

    Related Publications:

    Lallemant, D., Soden, R., Rubinyi, S., Loos, S., Barns, K., Bhattacherjee, G. (2017) Post-disaster damage assessments as catalysts for recovery: A look at assessments conducted in the wake of the 2015 earthquake in Nepal. Earthquake Spectra. (accepted 2017)

    Lallemant, D., Keiko, K., Nepal, G., Mainali, G., “Nepal 2015 Earthquake Post Disaster Needs Assessment – Housing and Human Settlement Sector Report”, Government of Nepal National Planning Commission (2015).

    McNaughton, E., Lallemant, D., Wills, J. (2015), “Leading in Disaster Recovery – A Companion through the Chaos.” Book on disaster recovery leadership. Red Cross Global Disaster Preparedness Center. DOI: 10.13140/2.1.4764.3689

    Lallemant, D., (2014). “Supporting and Informing the Process of Risk Arbitration in Post-Disaster Recovery” Conf. Proceedings and Plenary Talk, Third International Conference on Urban Disaster Recovery, Sept 28-Oct 1st, 2014. Boulder Colorado.

    Lallemant, D., (2013), Chapter title: “Risk Reduction in Post-Disaster Reconstruction,” pages 80-98 in report “Analyzing the Haiti Post-earthquake Shelter and Housing Response: What was Done and What Was Learned?,” The World Bank Publications.

    Lallemant, D. (2011). “Urban Reconstruction in a Challenging Environment – The Case of Haiti”, Invited Presentation, World Reconstruction Conference & Global Platform for Disaster Risk Reduction, Geneva 2011, May 10-13, Geneva, Switzerland.

    Lallemant, D. (2010). “Observations of Post-Disaster Reconstruction Efforts Following the 2010 Haiti Earthquake”, Invited Presentation, Massachussetts Institute of Technology, June 29th, 2010.

    Various blog posts on ResilientUrbanism.org