Volume 49-2 Complete Issue,
2024
Kutztown University of Pennsylvania
Volume 49-2 Complete Issue, Steven M. Schnell
The Geographical Bulletin
Volume 49-2 Complete Issue
The Power Of Place: Geography, Destiny, And Globalization’S Rough Landscape, By Harm De Blij,
2024
University of New Orleans
The Power Of Place: Geography, Destiny, And Globalization’S Rough Landscape, By Harm De Blij, James Lowry
The Geographical Bulletin
I have come to expect a great deal from Harm de Blij over the years and he has always delivered. So, when I was presented the opportunity to review this new look at globalization from the de Blij perspective I jumped at the chance. The purpose of The Power of Place is to examine the many assertions of a flattening of the earth; of the globalization we are constantly being told is leading us to a loss of regional cultures. So how does de Blij accomplish this task considering the flattening of the earth has been widely recognized as gospel? …
Spring Valley, Washington Dc: Changing Land Use And Demographics From 1900-2000,
2024
United States Military Academy
Spring Valley, Washington Dc: Changing Land Use And Demographics From 1900-2000, Benefsheh D. Verell
The Geographical Bulletin
Spring Valley, located in northwest Washington D.C., has had a dynamic land use history, changing from farmland to military base to residential development during the span of one hundred years. The development and marketing of Spring Valley in the 1930s and 1940s reflects the changing socioeconomics and settlement patterns of D.C. The data suggest a “white flight” out of the inner-city neighborhoods to Spring Valley and the surrounding suburbs. Additionally, Spring Valley, as a Formerly Used Defense Site, presents environmental hazards to the current residential community. The Army’s response to this hazard demonstrates changes in military environmental policies from nonexistent …
Predicting Paths Of Atlantic Tropical Cyclones Using Monthly Surface Pressure Data,
2024
Mississippi State University
Predicting Paths Of Atlantic Tropical Cyclones Using Monthly Surface Pressure Data, P. Grady Dixon, Michael E. Brown, W. Michael Carter, W. Scott Gunter, Kelsey N. Scheitlin
The Geographical Bulletin
Previous research has had some success in predicting likely tracks of tropical cyclones in the Atlantic basin using North Atlantic Oscillation (NAO) anomalies (above or below average values) during preceding months. This paper expands on this research by incorporating other surface pressure values as independent variables as alluded to by some of the earliest NAO research. We examine monthly sea-level-pressure (SLP) data from Reykjavik (Iceland), Cape Hatteras (North Carolina), and Nassau (Bahamas), along with NAO index anomalies, to see if they can be used to predict future paths and landfall locations of Atlantic tropical cyclones during the period 1970–2005. Average …
Remote Sensing Quantification Of Wetland Habitat Change In South Carolina: Implications For Coastal Resource Policy,
2024
Western Kentucky University
Remote Sensing Quantification Of Wetland Habitat Change In South Carolina: Implications For Coastal Resource Policy, John All, Jenna Nelson
The Geographical Bulletin
Increased urbanization of coastal areas has resulted in the pollution and destruction of wetland ecosystems worldwide. The effect of development on local wetland habitat was examined for Mount Pleasant, South Carolina, USA. Changes in the areal extent of wetlands in Mount Pleasant were determined through a quantification of changes in wetland margins from the 1970s to 1990s using Landsat data. The rate of wetland habitat loss accelerated from the 1980s to 1990s compared to the 1970s, even though coastal zone regulations had been strengthened and the rate of population increase was comparable for the decades selected for comparison. This paper …
Assessing A Small Summer Urban Heat Island In Rural South Central Pennsylvania,
2024
Shippensburg University
Assessing A Small Summer Urban Heat Island In Rural South Central Pennsylvania, Danielle Doyle, Timothy W. Hawkins
The Geographical Bulletin
The development of cities potentially has a significant impact on climate. Buildings and infrastructure that replace natural vegetation often create new microclimates through changes in the energy balance associated with the built environment. The urban heat island effect, the phenomenon where air temperatures within an urban area are warmer than the surrounding rural areas, has been thoroughly examined for large urban areas. The purpose of this study is to determine the magnitude and extent of the urban heat island for a small urban area surrounded by agricultural land. Temperature data collected from several urban and rural locations over a four-month …
Explainable Artificial Intelligence To Interpret Spatially-Explicit Impacts Of Future Climate Change On Species Distribution,
2024
University of California, Santa Barbara
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,
2024
University of Colorado Boulder
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 …
Enhanced Lithological Mapping In Arid Crystalline Regions Using Explainable Ai And Multi-Spectral Remote Sensing Data,
2024
Chapman University
Enhanced Lithological Mapping In Arid Crystalline Regions Using Explainable Ai And Multi-Spectral Remote Sensing Data, Hesham Morgan, Ali Elgendy, Amir Said, Mostafa Hashem, Wenzhao Li, Surendra Maharjan, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Lithological classification is essential for understanding the spatial distribution of rocks, especially in arid crystalline areas. Artificial intelligence (AI) recent advancements with multi-spectral satellite imagery have been utilized to enhance lithological mapping in these areas. Here we employed different AI models namely, Support Vector Machine (SVM), Random Forest Classification (RFC), Logistic Regression, XGBoost, and K-nearest neighbors (KNN) for lithological mapping. This was followed by the application of explainable AI (XAI) for lithological discrimination (LD) which is still not widely explored. Based on the highest accuracy and F1 score of the previously mentioned models, RFC model outperformed all of them, and …
Collaborative Professional Development Featuring Innovative Curriculum Materials,
2024
University of Alabama - Tuscaloosa
Collaborative Professional Development Featuring Innovative Curriculum Materials, Cory Callahan
The Councilor: A National Journal of the Social Studies
Here I synthesize two research investigations (Callahan, 2018, 2019) that comprise a continuing line of inquiry into the potential of innovative curriculum materials and sustained collaboration as a professional development program to help in-service teachers understand and implement a complex model of social studies instruction. This article features an original innovative curriculum material and specifically explores the question: To what degree can a collaborative professional development program featuring innovative curriculum materials help social studies teachers understand and implement a powerful social studies approach? Findings suggest the professional development program and its innovative curriculum materials helped teachers promote substantive pedagogical thinking …
Understanding Complex Socio-Environmental Systems With Spatial Agent-Based Models,
2024
University of Illinois at Urbana-Champaign
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,
2024
University of California, Santa Barbara
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,
2024
Virginia Polytechnic Institute and State University
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,
2024
University of Illinois at Urbana-Champaign
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,
2024
University of Illinois at Urbana-Champaign
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,
2024
University of Illinois at Urbana-Champaign
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. …
Note From Editor,
2024
Kutztown University of Pennsylvania
Cover And Forewords,
2024
Kutztown University of Pennsylvania
Interview: Interviewed By Steven Schnell Editor, The Geographical Bulletin,
2024
Kennesaw State University
Interview: Interviewed By Steven Schnell Editor, The Geographical Bulletin, Thomas J. Baerwald
The Geographical Bulletin
Tom Baerwald is currently President of the Association of American Geographers, and is employed at the National Science Foundation, where he has served in many capacities, most recently as Senior Science Advisor in the Division of Behavioral and Cognitive Sciences and as a program director for the Geography and Regional Science Program. He also is a coordinator for environmental social and behavioral science activities, assisting in the conduct of multidisciplinary efforts that engage social and behavioral scientists in the studies of interactions among human and natural systems. He earned a B.A. in geography and history from Valparaiso University and both …
Development Of A Severe Winter Index: Buffalo, New York,
2024
CBS4
Development Of A Severe Winter Index: Buffalo, New York, Theodore Mcinerney, Stephen Vermette
The Geographical Bulletin
Climate indices provide a useful way to characterize climate. The objective of this study is to rank the past 37 winters (1970-1971 to 2006-2007) in Buffalo, New York using a ‘Severe Winter Index’ (SWI) that incorporates a number of winter-related elements. Five elements were chosen to reflect varying aspects of a winter season: snowfall amount, number of days with 12 inches or greater of snow on the ground, heating degree days (HDD), number of days with temperatures at or below 0o F, and percent cloudiness during daylight hours. Data were obtained from the Buffalo Forecast Office of the National Weather …
