Authors: Zeliu Zheng*, Louisiana State University
Topics: Human-Environment Geography, Quantitative Methods
Keywords: community resilience
Session Type: Poster
Presentation File: No File Uploaded
Louisiana’s coastal communities face tremendous challenges related to severe weather events, threatened ecosystems, inundation, rising sea levels, hazardous spills, and land subsidence. The challenges to physical safety and the livelihoods of coastal citizens in both rural and urban areas of the Louisiana coast are similar. No communities are homogeneous in their strengths and struggles. This project aims to understand better what recovery looks like for each community through a comparison of pre-disaster and post-disaster capacities. This research creates a disaster resilience index to measure the variation and capacity gaps among three coastal Louisiana Parishes before and after the south Louisiana flooding event of August 2016 to better understand how each community could be aided in developing a plan for future resilience. Base on previous research on community resilience, this research re-examines variables in the index chosen by previous researchers. Whether the category generated by empirical studies the same as principal components automatically generated in the principal component analysis? How Factor Analysis may provide different results compare to principal component analysis if these two methods were considered similar to distinctive difference? How does the Random Forest and analysis solve some initial weighting problems compare to all these previous methods? This paper uses the post-flood data to test the random forest method to provide a comparison between these methods. In order to make a contribution to generating a more reasonable community resilience index.
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