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Characterizing Disaster Resilience Using Very High Resolution Time-Sequence Stereo Imagery

Julius, Alexandria Marie
http://orcid.org/0000-0003-2730-5448
http://rave.ohiolink.edu/etdc/view?acc_num=osu1524211742718203

Abstract Details

2018, Master of Science, Ohio State University, Civil Engineering.
As urbanization increases in cities prone to earthquakes, increasing disaster resilience, or the ability to absorb shock of the disaster, is increasingly important to preserve the integrity of critical infrastructure and save human lives. This study explores the response and resilience of Haiti following the 2010 M7.0 earthquake. Traditional methods of measuring resilience following a major earthquake require census data. Census data is seldom available at a great level of detail. As an alternative to census data, satellite imagery provides an objective measurement of the history of the earth, consistent both in temporal and spatial resolution. The currently available Very High Resolution (VHR) remote sensing sensors observe objects on the ground as small as 0.3 meters. The additional dimensions of volume and shape of the buildings provide the ability to distinguish building functions when compared to the traditional two-dimensional data. From the land cover and land use classification results for each year, a time series analysis analyzes the changes through the years of the individual buildings and building types. Using the building type classification results, the changes in resilience indicators are analyzed by year. Elasticity, amplitude, and malleability are the three indicators used to measure resilience. Elasticity refers to the recovery duration of the city to a stable state after the earthquake; Amplitude refers to the changes in the built-up area caused by the earthquake, essentially how much the city is impacted by the earthquake; finally, malleability refers to the city’s new development after the earthquake, compared to its original state. The results are compared to census data to illustrate the correlations between the observed dynamics and the given data, as well as to draw conclusion about the recovery processes. Using satellite images to characterize the resilience of a built-up area is feasible, and change detection analysis can be used to do a change series analysis of imagery spanning an earthquake. This analysis found that the recovery of the building system in Haiti could be characterized as elastic, as it increased to pre-shock levels following the earthquake, and malleable because there was not a net negative difference in the building area; Looking at amplitude, the city did not reach the threshold level of strain that prevented return to the original state. While the definitions of the three resilience indicators would lead a reader to believe that Haiti was resilient to the impact of the 2010 earthquake, future work needs to be done to disaggregate the effects of increasing urbanization and development that were occurring regardless of the earthquake from the impact of the earthquake itself. Overall, this project provides a case study that there is capacity to carry out traditional resilience analysis in areas without substantial census data, but that more datasets in the time series analysis are necessary in the years prior to the earthquake. The methods can be improved to be applied in the case of future global earthquakes, addressing questions of resilience in a more comprehensive and timely manner.
Rongjun Qin (Advisor)
Desheng Liu (Advisor)
Alper Yilmaz (Committee Member)
87 p.
Civil Engineering
Land cover and Land use; Classification; Photogrammetry; Remote Sensing; Mapping; Satellite Imagery; Multispectral Orthophotos; Digital Surface Model; Time Series Analysis; Haiti; Resilience Quantification; Disaster Resilience

Recommended Citations

Citations

  • Julius, A. M. (2018). Characterizing Disaster Resilience Using Very High Resolution Time-Sequence Stereo Imagery [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524211742718203

    APA Style (7th edition)

  • Julius, Alexandria. Characterizing Disaster Resilience Using Very High Resolution Time-Sequence Stereo Imagery. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1524211742718203.

    MLA Style (8th edition)

  • Julius, Alexandria. "Characterizing Disaster Resilience Using Very High Resolution Time-Sequence Stereo Imagery." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524211742718203

    Chicago Manual of Style (17th edition)

osu1524211742718203
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This open access ETD is published by The Ohio State University and OhioLINK.