Spatial-temporal assessment of resilience in Uganda

Climate shocks and stresses are important constraints to local resilience and sustainable development. This dissertation integrates household panel data and natural hazard risk modeling to enable a more precise geographical comparison of resilience levels as a function of place-based vulnerability. As a case study using multiple methods, it contributes to the science of disaster resilience by analyzing household spatial-temporal determinants of resilience to examine changes in welfare outcomes. This in turn provides evidence of the effectiveness of using resilience as a criterion for assessing changes in welfare over time.;Through the use of panel data, the study's main findings include: (1) Cross-sectional analysis of household resilience indicates that environmental risks, as captured via hazardous risk assessment, influence resilience outcomes and merit consideration. (2) Socioeconomic and environmental linkages are observed through the lens of subsistence farming, on which 46 percent of Ugandan households depend for their main livelihood strategy. (3) Using dietary diversity scores as the test variable, clear transitions from unstable to stable states, as well as the inverse, were observed. The examination of such transitions is valuable as it enables targeted assistance planning and monitoring to identify emerging areas of food insecurity. (4) Observed variables were ranked to identify the strongest predictors of resilience and potential leading indicators for changes in wellbeing. The highest ranking variables include: instances of financial aid accepted in the prior 12 months; changes in savings; instances of physical, mental, or emotional disability; and dietary diversity. Threshold scores enabled omission of six variables to compute the resilience index, thereby reducing the number of observed variables needed and increasing the efficiency of future data collection. The results were validated using panel data modeling. (5) Longitudinal analysis revealed the importance of measuring resilience levels at subsequent periods, noting that the drivers of resilience shift and change with shocks and over time. Additional work is needed to assess temporal effects and ensure high quality, representative data is available to facilitate ongoing monitoring.;Finally, this study demonstrates a method for using geographic information system overlays of household and natural hazard data to identify discrete risk areas with inherent vulnerability. Spatial and temporal knowledge of specific resilience factors provides a sound basis for decision-making and assists with the design of effective policies and targeted interventions. The study's results are intended to contribute to efforts to refine the process of measuring and assessing resilience. The goal is to provide for more informed policy decisions to enhance resilience and greater guidance for localized, sustainable practices designed to mitigate the impact of disasters.