Digital Commons Network^™

Studying Extreme Weather Event Impacts For Transit-Reliant Unhoused Populations, Costanza Rampini, Serena Alexander, Jeff Wootton, Amruta Ashish Gandhi

Mineta Transportation Institute

No abstract provided.

Heat And Socioeconomic Deprivation Compound To Drive Coronary Heart Disease In Los Angeles, Shutong Huo, Tessa R. Pulido, Reginald S. Archer, Joshua B. Fisher, Jason A. Douglas

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Background:

Socioeconomic deprivation and environmental heat exposure each increase cardiovascular risk, yet evidence is limited on how these stressors co-occur and jointly shape disease burden within cities. Mapping their overlap can inform equity-oriented planning and needs-based allocation of health and social protection resources.

Methods:

We conducted an ecological geospatial analysis of 2,513 census tracts in Los Angeles County. Adult coronary heart disease (CHD) prevalence was obtained from CDC Population Level Analysis and Community Estimates (2021). Socioeconomic deprivation was measured using the Social Deprivation Index (SDI), and heatwave surface heat hazard was measured using land surface temperature (LST) retrieved from the …

Gis Librarians' Involvement In Critical Information Literacy Instruction, Melissa Chomintra, Pete E. Pascuzzi

Libraries Faculty and Staff Scholarship and Research

Critical information literacy (CIL) is a theory and practice that considers the sociopolitical dimensions of information and knowledge production. As the field of geospatial information evolves, equipping librarians with the skills to critically engage with geospatial information becomes integral to facilitating informed research, promoting spatial literacy, and strengthening the accessibility of geospatial data for their user communities. To understand geospatial data librarians’ current involvement in CIL, librarians were surveyed to examine if they incorporate CIL into their instruction, how they incorporate CIL into their instruction, and what are the benefits and challenges of doing so. The survey gathered both quantitative …

Addressing Socioeconomic Disparities In The Treatment Of Antimicrobial-Resistant Infections: The Role Of Pharmacists In Mitigating Barriers, Arin Wade, Danielle Egbujor, Anna Spalvieri, Owen Fox, Marisa Petrunich, Joshua Honaker, Samantha Mccord, Kasie Landin

Pharmacy and Wellness Review

Antimicrobial resistance is an escalating global threat driven by inappropriate antibiotic use and shaped by socioeconomic disparities. Social determinants of health, including limited healthcare access, poverty, low health literacy, and environmental conditions, contribute to higher rates of resistant infections and poorer treatment outcomes in underserved populations. Barriers such as pharmacy deserts, self-medication, and inadequate stewardship infrastructure amplify these risks. Pharmacists, as accessible and highly trained healthcare professionals, play a critical role in combating antimicrobial resistance by optimizing antibiotic use, delivering culturally competent education, and leading antimicrobial stewardship programs across settings. Community and clinical pharmacists are especially well positioned to bridge …

Towards The Next Generation Of Geospatial Artificial Intelligence, Gengchen Mai, Yiqun Xie, Xiaowei Jia, Ni Lao, Jinmeng Rao, Qing Zhu, Zeping Liu, Yao-Yi Chiang, Jiao, Junfeng

Research Collection College of Integrative Studies

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote …

Making Slums Legible, Visible And Calculable: Geospatial Technologies And The Governance Of Urban Land In Mumbai, Sanjana Krishnan

Theses and Dissertations--Geography

This dissertation examines how geospatial technologies are used to make slums in Mumbai legible, calculable, and hypervisible, and how these practices reshape urban land governance. It situates mapping, remote sensing, and algorithmic systems within their political-economic contexts, showing how technologies intending to see the city often function as instruments of dispossession. The research has three interconnected empirical chapters. The first empirical chapter traces the history of slum mapping in Mumbai, from their absences in early development plans to their selective hypervisibility under the contemporary governance regimes. Using critical cartographic methods, it highlights how novel technologies such as remote sensing, biometric …

A Dynamic Urban Digital Twin Integrating Longitudinal Thermal Imagery For Microclimate Studies, Vasantha Ramani, Marcel Ignatius, Joie Lim, Filip Biljecki, Clayton Miller

Research Collection College of Integrative Studies

Recently, the concept of a digital twin for the built environment has received significant attention due to its potential benefits to urban planners, engineers, and designers. The development of tools that aid in integrating real-world physical systems with digital capabilities is essential for advancing digital twin technology. In this work, we present one such digital twin tool that integrates the longitudinal thermal envelope data of buildings on the campus of the National University of Singapore with a virtual 3D model. Thermal images of the buildings were captured using a neighborhood-scale infrared observatory for a few months. The temperature profile of …

Projecting The Effects Of Climate Change And Urbanization On Longleaf Pine Stands In The Florida Flatwoods, Lilian Grace Hutchens

Theses and Dissertations

The southeastern United States once held millions of hectares of highly connected longleaf pine ecosystem. In a dramatic range reduction, longleaf pine now occupies less than 5% of its original extent, its remnant patches existing within a matrix of human-dominated land uses. Conservation planning for longleaf pine ecosystems is complicated given the ecosystem’s reliance on fire and the broad spatial and temporal scales at which longleaf pine management must operate. Planning timelines for longleaf pine management extend into the end of the 21st century, a period during which climate, fire regimes, and land cover are all expected to change, influencing …

Exploring Inequality At Copan, Honduras: A 2d And 3d Geospatial Comparison Of Household Wealth, Heather Richards-Rissetto

Department of Anthropology: Faculty Publications

The archaeological site of Copan was a cultural and commercial crossroads at the southeastern Maya frontier. Research indicates that the demographics and sociopolitical circumstances of the city of Copan and its location within a circumscribed pocket (24 km²) of the larger Copan Valley varied through time. These circumstances not only influenced its social, political, and economic interactions, but likely the size, construction, and organization of households, specifically plazuelas. Copan’s plazuelas differ from those located in other Maya regions because they often have smaller house platforms, comprise more than a single patio, and exhibit a larger than normal …

Machine Learning For Modeling Wildfire Susceptibility At The State Level: An Example From Arkansas, Usa, Abdullah Al Saim, Mohamed H. Aly

Geosciences Faculty Publications and Presentations

Fire susceptibility modeling is crucial for sustaining and managing forests among many other valuable land resources. With 56% of its area covered by forests, Arkansas is known as the "natural state". About 1000 wildfires occurred and burned more than 10,000 acres each year during 1981-2018. In this paper, we use remote-sensing-based machine learning methods to address the natural and anthropogenic factors influencing wildfires and model fire susceptibility in Arkansas. Among the 15 explored variables, potential evapotranspiration, soil moisture, Palmer drought severity index, and dry season precipitation were recognized as the most significant factors contributing to the fire density. The obtained …

‘Big’ And ‘Little’ Quo Vadis? In The United States, 1913–1916: Using Gis To Map Rival Modes Of Feature Cinema During The Transitional Era, Jeffrey Klenotic

Faculty Publications

This article emanates from a geospatial database of over 600 premieres of the Cines company’s Quo Vadis? (1913), an eight-reel film distributed by George Kleine, and nearly 250 premieres of the Quo Vadis Film Company’s Quo Vadis? (1913), a three-reel film of ambiguous origins distributed by Paul De Outo. By mapping local premieres of both films across the United States from 1913 through 1916, the data show with spatiotemporal precision the spread of Quo Vadis? as one of cinema’s early blockbuster titles. Yet within this national phenomenon, the two films’ footprints reveal differing cultural geographies served by competing efforts to …

Machine Learning & Big Data Analyses For Wildfire & Air Pollution Incorporating Gis & Google Earth Engine, Abdullah Al Saim

Graduate Theses and Dissertations

The climatic condition, the vegetation type, and the landscape of the United States have made it susceptible to wildfires. This research is divided into two parts based on the analysis of two different aspects of wildfires of two distinct regions. The first part of the study investigates the wildfire susceptibility in Arkansas. Arkansas is a natural state, and it is heavily dependent on its forest and agricultural resources. During the last 30 years, more than 1,000 wildfires occurred in Arkansas and caused more than 10,000 acres of burned areas. Therefore, identifying wildfire-susceptible areas is crucial for ensuring sustainable forest and …

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 …

Mapping Maya Hinterlands: Lidar Derived Visualization To Identify Small Scale Features In Northwestern Belize, Jeremy Mcfarland, Marisol Cortes-Rincon Ph.D.

Humboldt Journal of Social Relations

This paper will discuss the processes and methods of relief visualization of LiDAR-derived digital elevation models (DEM’s) and classification of secondary data to identify archaeological remains on the ancient Maya landscape in northwestern Belize. The basis of the research explores various Geographic Information System (GIS) and cartographic techniques to visualize topographical relief. Graphic terrain maps assist archaeologists with predictive settlement patterns. The Relief Visualization Toolbox (RVT 1.3) aids to visualize raster DEM datasets in the predictive identification and interpretation of small-scale archaeological features. This dataset and methodology can be utilized to answer questions of population estimates, mobility costs, and effectiveness …

Newsworthy Migrants: Sentiment And Text Analysis Of Dutch Newspapers, Nicholas J. Schmitz

Independent Study Project (ISP) Collection

Understanding how a migrant population is viewed and displayed by the host country has been a struggle for a long period of time for anyone studying migration. Traditional methods of collecting information were tedious, time intensive and expensive. However, Big data has been providing unique solutions to gaps in information in many different fields across the world. Media plays an important part in developing and assessing the public opinion on a topic. With the availability of a large number of online articles from historical time periods, it is possible to use quantitative analysis, such as text analytics, to can see …

Using Deep Learning To Forecast Spatiotemporal Crime Patterns, Shuzhan Fan

LSU Doctoral Dissertations

The distributional patterns of crime occurrences are closely related to their spatial, temporal, and environmental contexts. It has been a hot topic for researchers and crime analysts to discover such complex relationships in order to forecast crime, both spatially and temporally. Many factors play a role in the occurrences of crimes. Conventional crime forecasting research has primarily relied on historical crime records and socioeconomic data, while ignoring the rich social media and other environmental context data. The large volume of data requires a more appropriate forecasting framework with the ability to take in massive multimodal data and possibly achieve better …

Creating Singapore’S Longest Monthly Rainfall Record From 1839 To The Present, Elaine Gao, Bertrand Timbal, Fiona Williamson

Research Collection School of Social Sciences

Currently,the identification of decadal variability is limited by the lack of long-termmeteorological datasets; Singapore’s reliable contemporary network of automaticmeteorological stations (AWS) provides only about 30 years of rainfall data for thewhole island. In this study, rainfall data, sourced fromhistorical archives and recording monthly rainfall pre-dating the start ofofficial MacRitchie observations, are compiled from various locations acrossthe island. By making use of the contemporary AWS network, we evaluate thespatial relationship of rainfall between the historical sites and the currentMacRitchie site. This enables us to reconstruct historical rainfall atMacRitchie using the archive data, thereby building a single-location extendedrainfall record (though discontinuous) from …

A Geospatial Study Of The Drought Impact On Surface Water Reservoirs: Study Cases From Texas And California, Zachary Asbury

Graduate Theses and Dissertations

Drought in Texas and California has been a long-term problem. Over the past 60 years reservoir construction has occurred to remedy the situation. Satellite imagery has been used historically to measure and monitor fluctuations in surface water reservoirs. This investigation integrates remote sensing and geographic information system (GIS) technologies to study the impact of drought on selected surface water reservoirs in San Angelo and Dallas in Texas, and Lake Oroville in California. Expansion and shrinkage over the 2005-2016 period reveal the concrete impact that drought, along with other factors, have on the selected lakes. Fluctuations in reservoir sizes during summer …

Smartphone-Based Self Rescue System For Disaster Rescue, Xitong Zhou

Theses, Dissertations and Capstones

Recent ubiquitous earthquakes have been leading to mass destruction of electrical power and cellular infrastructures, and deprive the innocent lives across the world. Due to the wide-area earthquake disaster, unavailable power and communication infrastructure, limited man-power and resources, traditional rescue operations and equipment are inefficient and time-consuming, leading to the golden hours missed. With the increasing proliferation of powerful wireless devices, like smartphones, they can be assumed to be abundantly available among the disaster victims and can act as valuable resources to coordinate disaster rescue operations. In this paper, we propose a smartphone-based self-rescue system, also referred to as RescueMe, …

Spatiotemporal Computing For Enabling Scientific Research And Engineering Development: A Gis Practice, Chaowei Yang

Purdue GIS Day

No abstract provided.

A Critical Physical Geography Of Urban Soil Contamination, Nathan Mcclintock

Urban Studies and Planning Faculty Publications and Presentations

Anthropogenic lead (Pb) is widespread in urban soils given its widespread deposition over the course of the 19th and 20th centuries via a range of point- and non-point sources, including industrial waste and pollution, leaded paint, and automobile exhaust. While soil scientists and urban ecologists have documented soil Pb contamination in cities around the world, such analyses rarely move beyond proximal mechanisms to focus on more distal factors, notably the social processes mediating Pb accumulation in particular places. In this paper, I articulate a critical physical geography of urban soil Pb contamination that considers the dialectical coproduction of soil and …

Utilizing Landsat Tm And Oli In Predicting Oncomelania Hupensis Habitats Around Poyang Lake Before And After Three Gorges Dam Completion, Stephanie L. Mccracken

Honors Theses

Schistosomiasis is a parasitic disease caused by the Schistomsoma japonicum flatworm that utilizes the Oncomelania hupensis snail as an intermediate agent. In the People’s Republic of China, these amphibious snails contaminate freshwater systems infecting humans, bovines, and other mammals and have caused significant morbidity for over two thousand years (Wertheim, et al. 2012; Zhang, et al. 2012.) The gravity of this disease prompted the national government to initiate sizable public health programs, such as the World Bank Loan Project (WBLP.) In spite of WBLP's achievements, in 2004, after this program ended, a national survey acknowledged a resurgence of schistosomiasis in …

The Diseños Project: A Geospatial Visualization Of The Environmental History Of California, 1769-1892, Rubén Mendoza

SSGS Faculty Publications and Presentations

No abstract provided.

Landscape Epidemiology And Machine Learning: A Geospatial Approach To Modeling West Nile Virus Risk In The United States, Sean Gregory Young

Graduate Theses and Dissertations

The complex interactions between human health and the physical landscape and environment have been recognized, if not fully understood, since the ancient Greeks. Landscape epidemiology, sometimes called spatial epidemiology, is a sub-discipline of medical geography that uses environmental conditions as explanatory variables in the study of disease or other health phenomena. This theory suggests that pathogenic organisms (whether germs or larger vector and host species) are subject to environmental conditions that can be observed on the landscape, and by identifying where such organisms are likely to exist, areas at greatest risk of the disease can be derived. Machine learning is …

Old Dominion University Climate Change And Sea Level Rise Initiative, Spring 2012, Larry P. Atkinson (Editor)

CCSLRI Newsletters

Summer 2012 Newsletter of the Old Dominion University Climate Change and Sea Level Rise Initiative

Use Of Environmental Isotope Tracer And Gis Techniques To Estimate Basin Recharge, Abdulganiu A.A. Odunmbaku

Open Access Theses & Dissertations

The extensive use of ground water only began with the advances in pumping technology at the early portion of 20th Century. Groundwater provides the majority of fresh water supply for municipal, agricultural and industrial uses, primarily because of little to no treatment it requires. Estimating the volume of groundwater available in a basin is a daunting task, and no accurate measurements can be made. Usually water budgets and simulation models are primarily used to estimate the volume of water in a basin.

Precipitation, land surface cover and subsurface geology are factors that affect recharge; these factors affect percolation which invariably …