Evaluating The Impact Of Ai-Assisted Tools On Novice Interface Design For Combat Search And Rescue Operations, Louis Pandolfo, Kaylee H. Akerlund, Cassidi Ellison, Sierra Martinez

Discovery Day - Daytona Beach

Combat Search and Rescue (CSAR) operations are specialized military missions with the goal of rescuing personnel from hostile territory, often involving helicopters and elite teams tasked with locating and stabilizing survivors. It is imperative to a mission's success that any interface used by rescuers is efficient and usable, as they work under high risk, high stress, and time limited conditions. This study examined how access to artificial intelligence (AI) design tools influence novice interface design under a time constraint. Participants completed an interface design exercise based on a simulated U.S. Navy maritime disaster and CSAR mission. The overall aim of …

Geospatial Governance Failures In The Department Of Defense: Contractor Noncompliance, Ai Adoption, And The Parallel Treatment Of Gis And Cybersecurity, Lyndsey Olmstead

Geography and the Environment: Graduate Student Capstones

The Department of Defense's treatment of geographic information systems and cybersecurity as parallel rather than integrated policy domains produces geographically predictable vulnerability patterns across its global military installation footprint. This capstone investigates that conclusion through original spatial analysis, constructing a five-variable composite geospatial vulnerability index across the six U.S. Combatant Command regions using publicly available unclassified data. EUCOM ranked highest overall, driven by GPS/PNT spoofing density, commercial satellite coverage, and cyber incident frequency; CENTCOM ranked second, driven by OSINT exposure incidents and governance risk. The null hypothesis of random geographic distribution is rejected. Findings confirm the structural governance gap documented …

Radar Precursors To Severe Weather Reports In Left-Moving Supercells, Eric A. Carothers

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

While much research has examined dual-polarimetric signatures of right-moving supercells, very little has been done with left-moving supercells. Given that left-moving supercells are thought to be disproportionate producers of large hail, understanding their internal dynamics is vitally important. This study examines differences and trends in the dual-polarimetric signatures of left-moving supercells to identify precursors to severe weather reports. A dataset of left-moving supercells associated with severe weather reports was created. These storms are processed with an automated analysis algorithm that identifies and quantifies the polarimetric signatures in each storm. A method for analysis of differences and trends in their dual-polarization …

Performance Of Acoustic Telemetry And Space Use Of Pallid Sturgeon In The Lower Platte River, Nebraska, Christopher F. Pullano

School of Natural Resources: Dissertations, Theses, and Student Research

Pallid Sturgeon (Scaphirhynchus albus) are centenarian, potamodromous, rheophiles that historically occupied the Missouri River and Mississippi River basins. Listed on the U.S. Endangered Species Act in 1990, population declines are attributed to habitat fragmentation and degradation, as well as overharvest, and hybridization. A knowledge gap exists regarding the extent to which tributaries facilitate key life stages for Pallid Sturgeon. This study evaluated the capacity of acoustic telemetry to monitor the movements of Pallid Sturgeon in a shallow, braided tributary to the Missouri River. The specific objectives were to (1) evaluate the environmental variables influencing the performance of acoustic …

Impact Of Weather Systems On Uav Parameters Using Computational Fluid Dynamics, Saif Aljuhaishi, Yaseen K. Al-Timimi, Basim I. Wahab

Karbala International Journal of Modern Science

Since drones cannot fly in any kind of weather, they are not safe for time-sensitive activities. The study examines how the passage of weather systems in Iraq leads to the ban on drone flights, and how these weather conditions impact the aerodynamic forces of the drone. Hourly climate data for the study area were obtained from ECMWF ERA5 and CAMS in NetCDF format for four climate stations (Erbil, Baghdad, Rutbah, and Basrah). A ScanEagle drone was chosen for this study. The Python programming language was used to perform mathematical operations to calculate the ban on drone flights. ArcGIS 10.8 was …

Road Extraction On Remote Sensing Imagery: Historical Mapping Of The Brazilian Amazon, Jonas Paiva Botelho Jr

Graduate Theses/Dissertations

This work proposes an artificial intelligence model based on U-Net architecture to map road networks in the Brazilian Amazon. Over the years, the Amazon region has been heavily exploited, leading to increased deforestation rates, contributing to CO2 emissions, amplifying global warming, and causing a disturbance in local fauna and flora. The expansion into the forest by illegal miners, loggers, and land grabbers can be tracked down by the construction of roads, which we can refer to as the arteries of deforestation. Previous works on the matter proposed algorithms that use high-resolution imagery to map roads precisely. However, this work approach …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

A Graphical User Interface Using Spatiotemporal Interpolation To Determine Fine Particulate Matter Values In The United States, Kelly M. Entrekin

Honors College Theses

Fine particulate matter or PM2.5 can be described as a pollution particle that has a diameter of 2.5 micrometers or smaller. These pollution particle values are measured by monitoring sites installed across the United States throughout the year. While these values are helpful, a lot of areas are not accounted for as scientists are not able to measure all of the United States. Some of these unmeasured regions could be reaching high PM2.5 values over time without being aware of it. These high values can be dangerous by causing or worsening health conditions, such as cardiovascular and lung diseases. Within …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Hydrological Drought Forecasting Using A Deep Transformer Model, Amobichukwu C. Amanambu, Joann Mossa, Yin-Hsuen Chen

University Administration Publications

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were …

Pluto In Hand: Design And Implementation Of A Location-Based Mobile Augmented Reality Application For Viewing Open Data, Matthew O. Ward

Theses and Dissertations

Immersive mobile augmented reality (AR) technology has improved while geolocational data volume has grown. City governments can utilize this technology to share their geospatial data with the public, promoting smart city aims. This research describes the design and implementation of a novel open-source ARGIS application to view property tax lot information in New York City. This proof-of-technology demonstrates web-based AR can visualize location-based spatial data.

The Spatial Effects Of Elderly Population Presence On Covid -19 Incidence In Dki Jakarta Before, During, And After Large-Scale Social Restriction, Chotib Chotib, I G A A Karishma Maharani Raijaya Mrs., Ahmad Aki Aki Muhaimin Mr., Novani Saputri

Smart City

ABSTRACT

Infected cases and suspect cases of covid-19 are increasing more and more daily. This increment happens either in whole regions of Indonesia and DKI Jakarta as a capital city. The purpose of this research is to seek the pattern in spatial of Covid-19 incidence with 3 different periods of before, during, and after large-scale social restriction, and to identify the influence of the presence of the elderly and other factors. One of the scopes of this study is the presence of the elderly because the elderly population is considered as influencing the increase of Covid-19 incidence. The analysis method …

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

Ensemble Encoder-Decoder Models For Predicting Land Transformation, Pariya Pourmohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In studying dynamic and complex processes which are influenced by a system of inter-connected driving variables, it is crucial to apply models that can learn the complexity of the interactions. Land transformation is one of such complex processes, prediction of which can help to mitigate severe climate situations and improve the resiliency of communities. In this study, a multi-spectral set of data cubes is used to capture various characteristics of a geographic region. Based on the data cube, a feature space is constructed using socio-economic attributes, terrain characteristics, and landscape traits of the study region. Two-dimensional and three-dimensional convolutional neural …

Philosophical Perspectives, Jochen Albrecht

Publications and Research

This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in …

3d Canopy Model Reconstruction From Unmanned Aerial System And Automated Single Tree Extraction, Hai Ha Duong

Graduate Theses/Dissertations

This project aims to develop and assess methodology for spatial modeling and extracting individual trees from high spatial resolution Digital Surface Model (DSMs) derived from unmanned aerial system (UAS) or drone-based aerial photos. Those results could be used for monitoring of vegetative response of forests, grasslands and vineyards to regional and localized fluctuations in climate and seasonality. The primary objective of this research is to extract 3D spatial information using drone-based aerial imagery through photogrammetric methods. UAS flights were taken place at phenologically critical times over several locations owned and managed by Missouri State University (MSU). The 3D DSM can …

Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan

Graduate Theses, Dissertations, and Problem Reports (ETD)

High spatial resolution (HR) (1m – 5m) remotely sensed data in conjunction with supervised machine learning classification are commonly used to construct land-cover classifications. Despite the increasing availability of HR data, most studies investigating HR remotely sensed data and associated classification methods employ relatively small study areas. This work therefore drew on a 2,609 km2, regional-scale study in northeastern West Virginia, USA, to investigates a number of core aspects of HR land-cover supervised classification using machine learning. Issues explored include training sample selection, cross-validation parameter tuning, the choice of machine learning algorithm, training sample set size, and feature selection. A …

@Yourlocation: A Spatial Analysis Of Geotagged Tweets In The Us, Ocean Mckinney

CMC Senior Theses

This project examines the spatial network properties observable from geo-located tweet data. Conventional exploration examines characteristics of a variety of network attributes, but few employ spatial edge correlations in their analysis. Recent studies have demonstrated the improvements that these correlations contribute to drawing conclusions about network structure. This thesis expands upon social network research utilizing spatial edge correlations and presents processing and formatting techniques for JSON (JavaScript Object Notation) data.

Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek

Graduate Student Theses, Dissertations, & Professional Papers

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, …

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

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 …

Temporal And Spatiotemporal Investigation Of Tourist Attraction Visit Sentiment On Twitter, Jose J. Padilla, Hamdi Kavak, Christopher J. Lynch, Ross J. Gore, Saikou Y. Diallo

VMASC Publications

In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists' emotions when visiting a city's tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and …

Optimization Of Geosynchronous Space Situational Awareness Architectures Using Parallel Computation, Michael S. Felten

Theses and Dissertations

Improving Space Situational Awareness (SSA) remains one of the DoD’s top priorities. Current research at the Air Force Institute of Technology (AFIT) has shown that modeling and simulation of Geosynchronous Earth Orbit (GEO) SSA architectures can identify optimal combinations of ground and space-based sensors. This thesis extends previous research by expanding design boundaries and refining the methodology. A genetic algorithm examined this increased trade space containing 1022 possible architectures. Experimental trials that would have taken over 100 years on a desktop computer were completed in weeks using a high-performance computer containing over 125,000 cores. The results of the optimizer clearly …

Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two-dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed …

Evaluating Relevance And Reliability Of Twitter Data For Risk Communication, Xiaohui Liu

Dissertations

While Twitter has been touted to provide up-to-date information about hazard events, the relevance and reliability of tweets is yet to be tested. This research examined the relevance and reliability of risk information extracted from Twitter during the 2013 Colorado floods using five different approaches. The first approach examined the relationship between tweet volume and precipitation amount. The second approach explored the relationship between geo-tagged tweets and degree of damage. In the third approach, the spatiotemporal distribution of tweets was compared with flood extent. In the fourth approach, risk information from tweets were compared with survey responses obtained in a …

Accuracy Evaluation Of The Canadian Openstreetmap Road Networks, Hongyu Zhang, Jacek Malczewski

Geography & Environment Publications

Volunteered geographic information (VGI) has been applied in many fields such as participatory planning, humanitarian relief and crisis management. One of the reasons for popularity of VGI is its cost-effectiveness. However, the coverage and accuracy of VGI cannot be guaranteed. The issue of geospatial data quality in the OpenStreetMap (OSM) project has become a trending research topic because of the large size of the dataset and the multiple channels of data access. This paper provides details on a national study of the Canadian OSM street network data for the assessment ofcompleteness, positional accuracy, attribute accuracy, semantic accuracy and lineage. The …

Aiddata Gis International Fellowship: Ghana West-Africa, Jason N. Ready

Sustainability and Social Justice

My internship, or fellowship as it was commonly referred to, was funded by a non-profit organization out of Williamsburg Virginia called AidData. This fellowship took place in in the country of Ghana, West-Africa beginning in May of 2016 and continued for 14 weeks with 40 hours each week. The objective of this internship was to provide in-depth training on the use of geographic Information Systems to Private and Public sectors within the country to allow for increased efficiency, and transparency through data visualization. In accordance with the requirement of Clark Universities GISDE master’s program this paper will delve into the …

Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae

The Summer Undergraduate Research Fellowship (SURF) Symposium

Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …

Past Meets Future: Combining Gis, 3d Technologies, And Legacy Data To Reanalyze Ceramics At Copan, Honduras, Stephanie Sterling, Heather Richards-Rissetto, René Viel

UCARE: Research Products

The archaeological site of Copán—a UNESCO World Heritage Site in Honduras—was a primary center for cultural and economic exchange in the Maya world from the fifth to ninth centuries. Our research investigates the sociopolitical climate of the city immediately preceding this collapse. This poster presents the results of a pilot study intended to evaluate the potential of using a combination of digital technologies and legacy data to reanalyze a subset of diagnostic ceramics from select sites outside of Copan’s urban core. Our methods involved:

(1) Applying photogrammetry to generate 3D models for approximately 30 potentially temporally-diagnostic ceramic types

(2) Digitizing, …

Overcoming Roadblocks In Introducing Virtual World Technology To High Schools, Casey Dylan Bailey

Graduate Theses and Dissertations

The EAST (Environmental And Spatial Technology) Initiative is a non-profit educational organization that provides students in over two hundred schools in eight states with access to advanced computing technologies for the purpose of enabling students to develop technical skills early and to produce solutions to local community problems. Although many high-end technologies are available through EAST, they are desktop solutions that individual students use and there are none that enable students within a school or between schools to collaborate.

This thesis is a saga that documents the identification and removal of many roadblocks to introducing a 3D multi-user virtual simulation …