Search Results

Assessment of Post-earthquake Building Damage Using High-resolution Satellite Images and LiDAR Data - a Case Study From Port-au-prince, Haiti
When an earthquake happens, one of the most important tasks of disaster managers is to conduct damage assessment; this is mostly done from remotely sensed data. This study presents a new method for building detection and damage assessment using high-resolution satellite images and LiDAR data from Port-au-Prince, Haiti. A graph-cut method is used for building detection due to its advantages compared to traditional methods such as the Hough transform. Results of two methods are compared to understand how much our proposed technique is effective. Afterwards, sensitivity analysis is performed to show the effect of image resolution on the efficiency of our method. Results are in four groups. First: based on two criteria for sensitivity analysis, completeness and correctness, the more efficient method is graph-cut, and the final building mask layer is used for damage assessment. Next, building damage assessment is done using change detection technique from two images from period of before and after the earthquake. Third, to integrate LiDAR data and damage assessment, we showed there is a strong relationship between terrain roughness variables that are calculated using digital surface models. Finally, open street map and normalized digital surface model are used to detect possible road blockages. Results of detecting road blockages showed positive values of normalized digital surface model on the road centerline can represent blockages if we exclude other objects such as cars.
Considerations for Global Development and Impact using Haiti as a Case Study
As the world becomes more connected, issues surrounding sustainable development are coming to the fore of global discussions. This is exemplified in strategies such as the United Nation's Sustainable Development Goals (SDGs), released in 2015, which created a framework for global development that defines specific goals for issues like poverty, climate change, and social justice. To complement the analysis that went into defining the SDGs, capital allocations around the world are becoming more impact focused so that the paradigm of development is shifting from donations to impact investments. The push for impact, however, has led to a homogenization of global challenges like reproductive health and poverty. This, in turn, has led to a standardization of information resulting in agencies designing interventions based on data and information that is misguided because of incorrect assumptions about a specific context. This paper explores how the decision-making mechanisms of global development agencies and investors could apply more anthropological processes to mitigate negative impact. As the development sector becomes more and more standardized, anthropologists can act as translators between affected communities and the institutions deciding how best to help them.
Back to Top of Screen