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Social and Behavioral Sciences Commons™

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Geography

University of South Carolina

2020

Articles 1 - 11 of 11

Full-Text Articles in Social and Behavioral Sciences

Application Of The Saffir-Simpson Hurricane Wind Scale To Assess Sand Dune Response To Tropical Storms, Jean Taylor Ellis, Michelle E. Harris, Mayra A. Román-Rivera, J. Brianna Ferguson, Peter A. Tereszkiewicz, Sean P. Mcgill Sep 2020

Application Of The Saffir-Simpson Hurricane Wind Scale To Assess Sand Dune Response To Tropical Storms, Jean Taylor Ellis, Michelle E. Harris, Mayra A. Román-Rivera, J. Brianna Ferguson, Peter A. Tereszkiewicz, Sean P. Mcgill

Faculty Publications

Over one-third of the Earth’s population resides or works within 200 km of the coast. The increasing threat of coastal hazards with predicted climate change will impact many global citizens. Coastal dune systems serve as a natural first line of defense against rising sea levels and coastal storms. This study investigated the volumetric changes of two dune systems on Isle of Palms, South Carolina, USA prior to and following Hurricanes Irma (2017) and Florence (2018), which impacted the island as tropical storms with different characteristics. Irma had relatively high significant wave heights and precipitation, resulting in an average 39% volumetric …

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Introduction To Big Data Computing For Geospatial Applications, Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan Aug 2020

Introduction To Big Data Computing For Geospatial Applications, Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan

Faculty Publications

The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for geospatial applications. Crucial to the advancements highlighted here is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms. This editorial first introduces the background and motivation of this …

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Immigrant Belonging In Belgium: Laws, Localities, And Living Together, Samuel P. Nielson Jul 2020

Immigrant Belonging In Belgium: Laws, Localities, And Living Together, Samuel P. Nielson

Theses and Dissertations

Nationalism is rising in Europe and the world. Much of it responds to massive migration, with nationalistic Europeans vocalizing their belief that immigrants do not “belong” in their countries. Many states respond to this influx of people and rising antiimmigrant sentiment by creating laws demanding immigrant “integration.” Yet a clear understanding of what defines “integration” remains elusive. So too does an understanding of how laws aimed at immigrant integration influence relationships between immigrants and local citizens, institutions, and spaces. This research addresses both of these points in Belgium, a politically and culturally fractured country that serves as a microcosm of …

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Spatio-Temporal Modeling Of Earthquake Recovery, Sahar Derakhshan Jul 2020

Spatio-Temporal Modeling Of Earthquake Recovery, Sahar Derakhshan

Theses and Dissertations

The recovery process after a major disaster or disruption, is impacted by the inequality of risk prior to and post event. In the past decades there has been few efforts to model the recovery process and the focus is mainly on staged models (i.e. emergency, restoration, and reconstruction). The overarching research question asks how a non-stage-like model could apply to the recovery process. This study poses three broad questions: 1) what are the indicators suitable for monitoring the recovery process; 2) what are the driving factors of differential recovery trends; and 3) what are the predicted development trajectories for communities …

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A 100 M Population Grid In The Conus By Disaggregating Census Data With Open-Source Microsoft Building Footprints, Xiao Huang, Cuizhen Wang, Zhenlong Li, Huan Ning May 2020

A 100 M Population Grid In The Conus By Disaggregating Census Data With Open-Source Microsoft Building Footprints, Xiao Huang, Cuizhen Wang, Zhenlong Li, Huan Ning

Faculty Publications

In the Big Data era, Earth observation is becoming a complex process integrating physical and social sectors. This study presents an approach to generating a 100 m population grid in the Contiguous United States (CONUS) by disaggregating the US census records using 125 million of building footprints released by Microsoft in 2018. Land-use data from the OpenStreetMap (OSM), a crowdsourcing platform, was applied to trim original footprints by removing the non-residential buildings. After trimming, several metrics of building measurements such as building size and building count in a census tract were used as weighting scenarios, with which a dasymetric model …

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Race And Urban Development Of Arsenal Hill, Sc, Samira Nematollahi Apr 2020

Race And Urban Development Of Arsenal Hill, Sc, Samira Nematollahi

Senior Theses

This thesis is a study on the Columbia neighborhood Arsenal Hill. It is one of the oldest neighborhoods in Columbia, but most of the neighborhood’s history is largely erased. In this paper, I studied the progression of change in Arsenal Hill with the goal of assessing who wielded power and to what extent race played a role in the neighborhood’s development. I find that race was the fundamental mover of change and that all other decisions and factors revolved around it. The initial decline of the neighborhood stemmed from its racial heterogeneity which then progressed into developers seeing Arsenal Hill …

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Remote Sensing And Social Sensing For Improved Flood Awareness And Exposure Analysis In The Big Data Era, Xiao Huang Apr 2020

Remote Sensing And Social Sensing For Improved Flood Awareness And Exposure Analysis In The Big Data Era, Xiao Huang

Theses and Dissertations

Floods are among the most devastating hazards on Earth, posing great threats to a large amount of population in the world. As the severity and frequency of flood events have noticeably increased, there is a growing need to improve the flood awareness and exposure analysis to assist flood mitigation. Fortunately, the Era of Big Data has fostered many innovative spatial data sources as well as spatial data analytics. This dissertation advances the existing flood monitoring studies by obtaining enhanced flood awareness via the development of a data fusion enable and deep learning supported flood monitoring framework that systematically integrates remotely …

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Remote Sensing Derived Indices For Tracking Urban Land Surface Change In Case Of Earthquake Recovery, Sahar Derakhshan, Susan Lynn Cutter, Cuizhen Wang Mar 2020

Remote Sensing Derived Indices For Tracking Urban Land Surface Change In Case Of Earthquake Recovery, Sahar Derakhshan, Susan Lynn Cutter, Cuizhen Wang

Faculty Publications

The study of post-disaster recovery requires an understanding of the reconstruction process and growth trend of the impacted regions. In case of earthquakes, while remote sensing has been applied for response and damage assessment, its application has not been investigated thoroughly for monitoring the recovery dynamics in spatially and temporally explicit dimensions. The need and necessity for tracking the change in the built-environment through time is essential for post-disaster recovery modeling, and remote sensing is particularly useful for obtaining this information when other sources of data are scarce or unavailable. Additionally, the longitudinal study of repeated observations over time in …

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Prototyping A Social Media Flooding Photo Screening System Based On Deep Learning, Zhenlong Li Huan Ning, Michael E. Hodgson, Cuizhen Wang Feb 2020

Prototyping A Social Media Flooding Photo Screening System Based On Deep Learning, Zhenlong Li Huan Ning, Michael E. Hodgson, Cuizhen Wang

Faculty Publications

This article aims to implement a prototype screening system to identify flooding-related photos from social media. These photos, associated with their geographic locations, can provide free, timely, and reliable visual information about flood events to the decision-makers. This screening system, designed for application to social media images, includes several key modules: tweet/image downloading, flooding photo detection, and aWebGIS application for human verification. In this study, a training dataset of 4800 flooding photos was built based on an iterative method using a convolutional neural network (CNN) developed and trained to detect flooding photos. The system was designed in a way that …

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A Gis-Based Risk Assessment For Fire Departments: Case Study Of Richland County, Sc, Tracy Whelen Jan 2020

A Gis-Based Risk Assessment For Fire Departments: Case Study Of Richland County, Sc, Tracy Whelen

Theses and Dissertations

Risk assessments enable fire departments to be better prepared for future incidents and to engage in more effective prevention activities. A combination of physical, demographic, and behavioral risk factors combined form a community’s level of risk. This research shows how spatial and nonspatial statistical methods can be used within a GIS framework to create such a risk assessment, with the Columbia-Richland Fire Department in Richland County, SC being used as a case study. Hot spot analysis and thematic mapping of incident rates were used to assess the first research question – what is the spatial variability of structure fires, carbon …

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Flooding And Industrial Swine Farming In North Carolina: Implications Of Natech Hazards On The Assessment Of Environmental Justice, Jacob Ramthun Jan 2020

Flooding And Industrial Swine Farming In North Carolina: Implications Of Natech Hazards On The Assessment Of Environmental Justice, Jacob Ramthun

Theses and Dissertations

“Natech” events, in which natural hazards trigger anthropogenic hazards, are becoming increasingly common. Methodologies for measuring the impact of natech events on environmental justice assessments are lacking, particularly in rural scenarios. This study used additive, multiplicative, and z-score threshold methods of combining the density of industrial swine farms in eastern North Carolina and the presence of flood risk to determine whether or not natech risk exhibits emergent socioeconomic indicators and whether areas of high natech constitute environmental injustice. The multiplicative and z-score threshold methods generated variables representing natech risk to compare to socioeconomic indicators, as well as statistically significant hotspots. …

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