Geographic Information Sciences Commons^™

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 …

Mapping Responsible Workflows For Geospatial Data Science: Developing The I-Guide Data Ethics Toolkit, Peter T. Darch, Kyra M. Abrams, Ivan Y M Kong

I-GUIDE Forum

AI workflows in geospatial data science offer significant societal benefits but raise ethical, transparency, and reproducibility challenges. Current ethical frameworks and tools are often hard to integrate into daily research practice. This paper introduces the I-GUIDE Data Ethics Toolkit (DET), a lightweight suite designed for users of the NSF-funded Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). Based on a longitudinal mixed-methods study, including surveys, interviews, and observations, we identified five design priorities: usability, anticipatory planning, distributed responsibility, comprehensive coverage, and policy compliance. We integrated existing AI and data research lifecycles into an eight-stage I-GUIDE Research Lifecycle, serving …

Evaluating The Evaluation Matrices: Integrating Spatial Assessment In Geospatial Ai Model Training And Evaluation, Fangzheng Lyu

I-GUIDE Forum

This paper examines the limitations of current evaluation metrics in GeoAI. Through two case studies on deep learning models—a building detection classification problem and a remote sensing image fusion regression problem—this paper demonstrates how traditional statistical evaluation matrices alone can be misleading in geospatial problems. The findings indicate that traditional metrics (e.g., RMSE, MAE) used in current GeoAI models can have difficulty capturing the spatial dimensions inherent to geospatial problems. This paper suggests that the model evaluation process in GeoAI should move beyond traditional evaluation matrices by integrating spatial thinking throughout the modeling pipeline—not only incorporating spatial accuracy in model …

Expanding Access To Cybergis-Compute Through Support For Heterogeneous Workflows, Alexander C. Michels, Ian Zhang, Anand Padmanabhan, John Speaks, Rebecca Vandewalle, Shaowen Wang

I-GUIDE Forum

CyberGIS-Compute is a geospatial middleware tool designed to lower technical barriers to High-Performance Computing (HPC) resources. It provides end-users with a Graphical User Interface (GUI) for submitting models to HPC and allows model developers to contribute their workflows by adding a manifest to their repositories. However, the simplification of the user interface and streamlining of model contribution have unintentionally limited the scope of models that could be run on CyberGIS-Compute. In this paper, we discuss recent developments to the CyberGIS-Compute project that are aimed at supporting a wider variety of workflows including performance enhancements, supporting additional configuration options for jobs, …

Assessing Vulnerabilities Associated With High-Risk Dams In Utah, Courtney Flint Dr., Michael Englert, Upmanu Lall Dr.

I-GUIDE Forum

Across the United States, the age of dam infrastructure presents a substantial threat. The potential for structural failure associated with these aging dams is exacerbated by increased climate uncertainty and the threat of dam overtopping due to extreme and prolonged precipitation events. These compound threats place downstream areas at pronounced risk. These downstream areas vary widely. Some are relatively free of vulnerable elements, while others have a complex mix of infrastructure, populations, and ecologically important elements. This paper highlights the risk situation associated with aging dams and hydroclimatic extremes, the methodological and geospatial challenges and opportunities associated with mapping the …

Explainable Artificial Intelligence To Interpret Spatially-Explicit Impacts Of Future Climate Change On Species Distribution, Lei Song, Amy E. Frazier, Peter Kedron, Diogo S. A. Araujo, Diyang Cui, Brian J. Enquist, Brian Maitner, Cory Merow, Gabriel M. Moulatlet, Efthymios I. Nikolopoulos, Patrick R. Roehrdanz

I-GUIDE Forum

Biodiversity is essential for maintaining ecosystem balance and functionality, providing vital services such as climate regulation. The rapid decline in biodiversity, driven by habitat loss, habitat fragmentation, and climate change, poses significant threats to ecosystems. Climate change, in particular, is fundamentally altering habitats, leading to shifts in species distributions. However, existing research often lacks decomposed contribution analyses, particularly spatially, for a changing individual environmental attributes when modeling species distribution as an aggregate result of all factors and their interactions. Such analyses are crucial for identifying climate refugia and prioritizing conservation efforts. Taking endangered mammal species as an example, this study …

Statistical Downscaling Of Climate Datasets With Deep Generative Model And Bayesian Inference, Guiye Li, Guofeng Cao

I-GUIDE Forum

Facing the challenges of global climate change, precise and high spatial resolution climate data are crucial and in pressing need for scientific research and analysis. However, most existing datasets are only available with very coarse spatial resolution and demand large-scale resolution enhancement. Meanwhile, climate datasets own much more intricate textures than natural images. Statistical downscaling or super-resolution (SR) with the deep-learning-based generative model might be a promising approach to address these challenges. It is worth noting that a learned Bayesian reconstruction with generative models (L-BRGM) method was proposed recently. The proposed Bayesian deep learning framework employs a single pre-trained generative …

Understanding Complex Socio-Environmental Systems With Spatial Agent-Based Models, Rebecca C. Vandewalle, Alexander Michels, Furqan Baig, Shaowen Wang

I-GUIDE Forum

Our increasingly connected world is faced with complex socio-environmental problems (e.g., biodiversity loss, climate change, and food insecurity). Tackling these problems requires cross- disciplinary approaches that examine the problems based on synergistic spatial and system thinking. Spatial Agent-Based Models (SABMs) represent a powerful approach to understanding complex socio-environmental systems. However, research on SABMs and associated complex problem solving face grand challenges that must be overcome to effectively unleash the power of SABMs enabled by cyber-based geographic information science and systems (cyberGIS). This paper describes four such grand challenges —reproducibility, scalability, communication, and accessibility. Resolving these challenges will enable new spatial …

Communicating Uncertainty And Cataloging Bias In Spatial Data Science Education, Peter Kedron, Jiahua Chen

I-GUIDE Forum

Uncertainty is an unavoidable part of any spatial analysis, which makes quantifying and communicating uncertainty a requirement of any spatial data science study. However, current curricula leave students understanding the importance of uncertainty and concerned about potential bias, but without an actionable framework to improve their workflows or inferences. We propose a framework rooted in Bloom’s Taxonomy for introducing these concepts to spatial data science students.

A Convergence Framework For Integrating Cybergis Education And Research On I-Guide Platform, Fangzheng Lyu, Furqan Baig, Yunfan Kang, Erick Li, Anand Padmanabhan, Shaowen Wang

I-GUIDE Forum

This paper described Data with Notebooks as a convergence framework for integrating cyberGIS education and research on the I-GUIDE Platform. The I-GUIDE Platform provides rich geospatial data and computing resources and adheres to FAIR (findable, accessible, interoperable, and reusable) data principles. The framework enhances these capabilities by harnessing scalable and reproducible geospatial analytics. Specifically, this framework supports the development of interactive cyberGIS education and research Jupyter Notebooks centered around geospatial datasets. A case study demonstrates the application of the framework, showing six cyberGIS research notebooks and four cyberGIS education notebooks based on a Twitter dataset. The case study and underlying …

Building Blocks For Geospatial Software Education Using The I-Guide Platform, Rebecca C. Vandewalle, Alexander Michels, Zhiyuan Li, Nattapon Jaroenchai, Shaowen Wang

I-GUIDE Forum

By combining advanced cyberinfrastructure with geospatial analysis capabilities and resources in an accessible online environment, the I-GUIDE Platform has great potential for geospatial computing focused education. However, learning occurs in different settings and contexts, both formal and informal. For I-GUIDE Platform to be successful, it should have the flexibility to support a variety of educational needs. In this paper, we argue for an expanded set of front-end building blocks to support diverse education and research use-cases, building on existing cyberGIS capabilities and Jupyter backend. We draw from experience working with the CyberGISX platform as an education tool in different learning …

Tradeoffs Of Generalization, Kyra M. Abrams, Peter T. Darch

I-GUIDE Forum

Models used in geospatial data science are often built and optimized for a specific local context, such as a particular location at a point in time. However, upon publication, these models may be generalized beyond this context, reused in research simulating or predicting other times and places. Without sufficient information or documentation, bias embedded in these models can in turn result in bias in the reuser’s research outputs. Drawing on a long-term qualitative case study of aging dams researchers and developers of models used by these researchers, we find significant documentation gaps. We combine a literature-based genealogy with interviews with …

Data-Intensive Convergence Science For Analyzing Place-Based Spatial Accessibility, Alexander C. Michels, Shaowen Wang

I-GUIDE Forum

Place-based spatial accessibility is a critical tool for measuring the health, resilience, and sustainability of communities. Accessibility methods are employed by a wide range of fields to measure access to food, healthcare, infrastructure and other critical needs. While measures of access are relatively simple, they attempt to capture the complexities of human mobility and spatial decision-making to assess how well populations are served by the infrastructure, resources, and services at their disposal. This paper describes four key areas where data-intensive convergence science can revolutionize our understanding of place-based spatial accessibility by addressing issues of scale, spatial impedance, diversity, and accessibility. …

Estimating Effects Of Tourism Using Multiple Data Sources: The Miranda Tool As Part Of A Spatial Decision Support System For Sustainable Destination Development, Tobias Heldt

GSTC Academic Symposium - In conjunction with the GSTC Global Conference

Planning for sustainable mobility and destination development in rural areas is increasingly important when tourism grows in numbers. A key to address the challenge of transformation and adaptation of local communities to mitigate adverse effects in seasonal peak hours like traffic congestion, power failure, waste management and sewage flooding, is to properly estimate the number of visitors to a destination.

The problem of estimating tourism numbers is a known challenge since, for example, guest nights statistics are in-complete and non-commercial lodging (sharing solutions) are increasing. Recently, the promising utilization of mobile phone data has emerged as a means to estimate …

Monitoring Of Caucasus Heritage Sites Facing Cultural Genocide, Peyton Edelbrock

The Journal of Purdue Undergraduate Research

No abstract provided.

Streamlined Hpc Environments With Cvmfs And Cybergis-Compute, Alexander C. Michels, Mit Kotak, Anand Padmanabhan, Shaowen Wang

I-GUIDE Forum

High-Performance Computing (HPC) resources provide the potential for complex, large-scale modeling and analysis, fueling scientific progress over the last few decades, but these advances are not equally distributed across disciplines. Those in computational disciplines are often trained to have the necessary technical skills to utilize HPC (e.g. familiarity with the terminal), but many disciplines face technical hurdles when trying to apply HPC resources to their work. This unequal familiarity with HPC is increasingly a problem as cross-discipline teams work to tackle critical interdisciplinary issues like climate change and sustainability. CyberGIS-Compute is middle-ware designed to democratize to HPC services with the …

Geospatial Data Integration Middleware For Exploratory Analytics Addressing Regional Natural Resource Grand Challenges In The Us Mountain West, Shannon Albeke, Nicholas Case, Samantha Ewers, Jeffrey Hamerlinck, William Kirkpatrick, Jerod Merkle, Luke Todd

I-GUIDE Forum

This paper describes CyberGIS-based research and development aimed at improving geospatial data integration and visual analytics to better understand the impact of regional climate change on water availability in the U.S. Rocky Mountains. Two Web computing applications are presented. DEVISE - Derived Environmental Variability Indices Spatial Extractor, streamlines utilization of environmental data for better-informed wildlife decisions by biologists and game managers. The WY-Adapt platform aims to enhance predictive understanding of climate change impacts on water availability through two modules: “Current Conditions” and “Future Scenarios”. It integrates high-resolution models of the biophysical environment and human interactions, providing a robust framework for …

An Agent-Based Modeling Approach To Spatial Accessibility, Alexander C. Michels, Shaowen Wang

I-GUIDE Forum

Place-based spatial accessibility represents the ability of populations within geographic units to access goods and services, and thus is an important indicator for sustainable development. Existing spatial accessibility models treat population as simply demand, calculating statistics or optimizing average cost for the population within each geographic unit, rather than modeling individual decisions. This paper proposes AgentAccess, a general-purpose Agent-Based Model (ABM) for spatial accessibility analysis. An ABM framework brings us closer to reality by simulating individual and imperfect decision-making. We introduce the model and compare its results against existing spatial accessibility models using a case study of hospital beds in …

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 …

Modeling Airport Catchment Areas: Using Spatial Analysis Approach, Sitong Chen

The Journal of Purdue Undergraduate Research

Th e airport catchment area is the geographic area from which an airport can reasonably expect to draw commercial air service passengers. Th e purpose of this interdisciplinary research is to estimate airport catchment areas using a spatial analysis method for informed airport management. In order to ensure the comprehensiveness and reliability of the research, we chose to analyze the catchment areas for five airports of different sizes and in different geographic locations in the United States. The Huff model, which is usually used in marketing, economics, and retail research, was adopted in this study. We applied this model in …

An Extensible Geospatial Data Framework (Geoedf) For Fair Science, Carol Song, Rajesh Kalyanam, Lan Zhao

Purdue GIS Day

The growing urgency in dealing with the 21st century’s grand challenges associated with increasing population, food and water security, frequently occurring natural disasters, and changing climate demands innovative, collaborative, and multidisciplinary solutions for sustainability and resilience. However, scientific data, especially geospatial data, presents significant barriers to the effective access, use and sharing of data as they come in large volumes, from different sources, and with widely varying formats, resolutions, or annotation schemas that can differ among disciplines or even research groups. This presentation describes a recently funded NSF CSSI project to develop an open source, extensible geospatial data framework (GeoEDF), …

Soil Erosion Analysis Of The Monroe County’S Watersheds In Indiana, Danielli De Melo Moura, Jie Shan

Purdue GIS Day

This study was carried out to spatially predict the amount of soil loss (tons/ha/year ) of Monroe County’s watersheds using Geographic Information System (GIS). Revised Universal Soil Loss Equation (RUSLE) was used to estimate potential soil losses by using information such as rainfall data for calculating the rainfall erosivity (R) , soil map for calculating the soil erodibility (K), digital elevation model for obtaining the topography factor (LS) and vegetation/cropland cover for calculating the cover management factor (C) and support practice factor (P). The result of the analysis depicted that the soil loss rate in Moroe’s watersheds ranges from 0 …

Effects Of Removing Background Soil Reflectance Pixels From Vegetative Index Maps For Characterization Of Corn Responses To Experimental Treatments, Ana Morales, Robert L. Nielsen, James J. Camberato

Purdue GIS Day

In contrast to traditional data collection methods that require manual sampling, vegetative index (VI) maps derived from unmanned aerial vehicles (UAV) imagery are a potential tool to characterize temporal and spatial treatment effects in a more efficient and non-destructive way. Remotely-sensed reflectance data from a growing corn crop contains pixel values associated with the above-ground plant tissue (e.g., leaves, stalks, tassels) and the underlying soil features. Background soil reflectance data potentially reduces the effectiveness of VI for characterizing crop responses to experimental treatments. Removing background soil image pixels from the larger image dataset should improve that effectiveness. The objective of …

Seeing A Better World From Space, Carly Sakumura

Purdue GIS Day

Understanding change is essential to addressing our most pressing global challenges. Organizations need actionable insight to make critical decisions that affect communities, economies, and national security. As a global leader of advanced geospatial and space-based technology solutions, Maxar has an unprecedented ability to observe, analyze, and monitor these global changes. In this talk, I’ll discuss the cutting-edge research, technological capabilities, and imagery products and analytics we develop at Maxar to unlock the power of geospatial data to understand and navigate our changing world.

Photogrammetric Measurement Of Hardwood Species At A Stand Level Using Rgb Images From Unmanned Aerial Vehicle (Uav), Aishwarya Chandrasekaran

Purdue GIS Day

Nowadays, for many remote sensing applications, drones are employed for gathering data, as it provides low cost image acquisition with minimal human intervention. Drone remote sensing has an extensive use in forestry for maintaining inventories, mapping canopy structure and monitoring forest fires. Maintaining a Forest inventory database is a crucial task as it is the only means of keeping a record of the trees. This study aims to explore UAV based image acquisition (consumer-grade sensor) and analysis for forest studies using structure from motion technique.The main objective is to derive a methodology for computing tree parameters such as tree height, …

Mapping Postcolonial Literature, Matthew Hannah, Yiqui Yan

Purdue GIS Day

Matthew Hannah (Assistant Professor of Digital Humanities) Yiqiu Yan (Undergraduate Researcher) Space and place are incredibly important features of the postcolonial novel and, for writers of the twentieth and twenty-first centuries who are living in former colonies, geography plays an incredibly significant role in navigating issues of identity, language, and nationality. Because the land is such a contested concept in postcolonial writing, we believe that attending to the localities described in literary representations of the land will provide a rich resource for theorizing the relationship between people and places, between colonies and nations. “Mapping Postcolonial Literature” will showcase an interactive …

Growth, Sprawl, And The Contradictions Of Capitalism: San Diego Suburbs And The Speculative Frenzy, 1970-1991, Richard Hogan

Purdue GIS Day

San Diego has become the most beautiful place where nobody can afford to live because speculative growth drives housing prices regardless of the level of supply or demand. How this happened in San Diego County is fairly clear. Marx explained that ground rents (and thereby land prices) increase when capital and labor are invested in the most valuable land and when investment is intensive, with vast amounts of labor and capital focused on the high yield properties to the virtual exclusion of less productive or less valuable lands. In fact, speculative growth between 1960 and 1980 conformed to what Marx …

Quantifying Four Decades Of Arid-Region Agricultural Development In Arequipa, Peru Using Landsat, Zachary S. Brecheisen, Nicholas Hamp-Adams, Edwin Bocardo Delgado, Martin Villalta Soto, Timothy Filley, Darrell G. Schulze

Purdue GIS Day

The Arequipa Nexus Institute for Food, Energy and the Environment (Nexus Institute) is located in Southwestern Peru, generally bounded by the city of Arequipa to the east, the Majes River to the west, the Pacific Ocean to the south, and the Andes mountains to the north. Though agriculture has been practiced in parts of this cool desert region (MAT~15°C, MAP

Visualizing Election Results With Arcgis, Ryan Day

Purdue GIS Day

In 2018, Porter County, Indiana held its municipal elections concurrent with the national midterm elections. Using ArcGIS, the election results for the fourway race for the Duneland School Board at-large seat are mapped. These results are compared to other area election results, voter characteristics, and previous election results to try to visualize the correlation between factors affecting the race, including candidate ideology, geographic base, area demographics, turnout, and national electoral trends. This project serves as a demonstration of how GIS software can improve the understanding of what influences voters and election outcomes.

The Value Of Open Gis In Higher Education, Christina Hupy

Purdue GIS Day

Open source software has become increasingly popular in geospatial research and industry. Despite this trend, higher education has less readily adopted open source in GIS curriculum which has been dominated by proprietary systems for decades. This presentation will discuss the value of bringing open source into GIS curriculum. The discussion will focus on several aspects including GIS curricular standards and competencies, employer demand, generational interest (millennials), pedagogical benefits, and general societal benefits. Strategies for encouraging the adoption of open source in GIS curriculum will be identified.