Social and Behavioral Sciences Commons^™

Estimation Of Economic Risk From Coastal Natural Hazards In Louisiana, Rubayet Bin Mostafiz

LSU Doctoral Dissertations

Louisiana, U.S.A., is among the most vulnerable areas globally to coastal natural hazards, with risk vulnerability likely increasing. The risks associated with non-tropical-cyclone hazards in Louisiana’s coastal zone have been understudied. This research enhances present and future (i.e., 2050) Louisiana risk assessment using locally-weighted, model-based hazard frequency/intensity and population projections.

Results suggest that property risks associated with extreme cold temperature and tornado are and will remain costlier than those for hail and lightning. Property risks of extreme cold temperature and hail are projected to decrease with the expected warming temperatures, with those of all four of these hazards peaking in …

Creating A Public Space For Georeferencing Sanborn Maps: A Louisiana Case Study, Adam Cox

LSU Master's Theses

As institutional archives digitize their historical map collections and make them publicly available online, new methods for engaging with these materials emerge. Georeferencing the maps transforms their content from static images to dynamic map overlays, and allows for the extraction of geographic data like building footprints or place name coordinates. Many organizations have turned to crowdsourcing to georeference their large holdings, and this thesis approaches crowdsourced georeferencing from the perspective of participatory heritage, taking much inspiration from the idea of the archival commons. To test these ideas, a new extension was created for GeoNode—an open source geospatial content management system—that …

Gis Automated Delineation And Analysis Of Cancer Service Areas In The United States, Changzhen Wang

LSU Doctoral Dissertations

Delineating a meaningful and reliable geographic unit pertaining to cancer care is essential in examining geographic variations in cancer care for better analysis, management, and planning. Public health researchers have devoted great efforts to defining various service areas, which; however, lack scientific rigor or are unrepresentative of the highly specialized cancer care markets, and their methods have become obsolete in the era of big data and high geo-computation. This study develops the “Spatially Constrained Leiden (ScLeiden)” method, a network community detection algorithm in Geographic Information Systems (GIS), and applies it to delineate a series of coherent cancer service …