Publicação
Assessing Social Inequity and Flood Susceptibility: A GIS-Based Spatial Statistical Approach: Integrating Social and Environmental Factors to Assess Flood Vulnerability in Harris County, Texas
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | pt_PT |
| dc.contributor.advisor | Painho, Marco Octávio Trindade | |
| dc.contributor.advisor | Costa, Ana Cristina Marinho da | |
| dc.contributor.advisor | Granell-Canut, Carlos | |
| dc.contributor.author | Vata, Flavio | |
| dc.date.accessioned | 2025-03-13T11:44:28Z | |
| dc.date.embargo | 2027-02-28 | |
| dc.date.issued | 2025-02-28 | |
| dc.description | Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies | pt_PT |
| dc.description.abstract | Flooding is one of the most severe climate-related hazards, disproportionately affecting vulnerable and marginalized communities. This study examines the intersection of social inequity and flood susceptibility in Harris County, Texas, through geospatial analysis and statistical modeling to develop a comprehensive flood vulnerability assessment. A Social Inequity Index (SII) is developed using Principal Component Analysis (PCA) on 34 socioeconomic and demographic variables, mapping and quantifying disparities in Harris County. Simultaneously, a Flood Susceptibility Map (FSM) is generated using the Analytic Hierarchy Process (AHP), incorporating ten key environmental and topographic factors that influence flood susceptibility; results reveal that nearly 30% of the county’s territory exhibits high flood susceptibility. To explore the spatial relationships between social inequity and flood susceptibility, this study employs advanced spatial statistical techniques, including hot spot analysis, Moran’s I, Geographically Weighted Regression (GWR), and Multiscale Geographically Weighted Regression (MGWR). By integrating the SII and FSM, a Flood Vulnerability Map (FVM) is produced, highlighting communities where social inequity exacerbates flood risk. Findings indicate that marginalized communities, particularly racial minorities such as African-American and Hispanic populations, as well as elderly individuals with disabilities, are disproportionately located in flood-prone areas. By bridging the gap between climate change hazards, social equity, and geospatial analytics, this research provides a novel framework for equitable disaster vulnerability assessment and management. The results provide critical insights for policymakers, urban planners, and disaster response agencies, enabling data-driven, targeted interventions that enhance community resilience against both flooding and social inequity. | pt_PT |
| dc.identifier.tid | 203924029 | |
| dc.identifier.uri | http://hdl.handle.net/10362/180542 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Flood Susceptibility | pt_PT |
| dc.subject | Social Inequity | pt_PT |
| dc.subject | Principal Component Analysis (PCA) | pt_PT |
| dc.subject | Analytic Hierarchy Process (AHP) | pt_PT |
| dc.subject | Geospatial Analysis | pt_PT |
| dc.subject | SDG 10 - Reduced inequalities | pt_PT |
| dc.subject | SDG 11 - Sustainable cities and communities | pt_PT |
| dc.subject | SDG 13 - Climate action | pt_PT |
| dc.title | Assessing Social Inequity and Flood Susceptibility: A GIS-Based Spatial Statistical Approach: Integrating Social and Environmental Factors to Assess Flood Vulnerability in Harris County, Texas | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | embargoedAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Tecnologias Geoespaciais | pt_PT |