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AGX Applied Geography Conference 2023: Building Community ConneXtions
Some Important Reminders:
Business Analyst Web is used daily in the business workplace for market planning, site selection, and understanding consumer lifestyle and purchasing. In education, it offers faculty and students a powerful, easy-to-use web-based toolset bundled with hundreds of fascinating variables at multiple scales for multiple countries. With nothing to install and as a part of most educational site licenses to which educators already have access, researchers, instructors, and students do not need to be GIS experts to take advantage of its capabilities. Join geographer Joseph Kerski in this engaging workshop as we create choropleth and drive-time maps, infographics, reports, and other compelling visualizations that foster understanding of patterns, relationships, and trends.
Environmental shifts caused by climate change are a major factor in the decline of bird species globally; since the 1970’s, close to 3.0 billion birds (~29%) have been lost in North America. Barn swallows’ niche nesting strategy makes them particularly vulnerable to climate change impacts such as drought. This study seeks to understand the connection between drought the observation density of Barn swallows in five regions, with delineation towards urbanity and rurality, in the Southwestern United States. The development of an anthropogenic mega-drought in the American Southwest will have continue to reap havoc on ecological systems and provides an opportunity for development of applied geographic approaches with citizen science data to detect and understand systemic stressors. This paper explores the impacts of drought on selected barn swallow observation density, the utilization of citizen science data use developing within applied geography, and the need for further integration of citizen science data analysis into applied geography. Pearson’s correlation coefficient was calculated for each observation density dataset. Data analysis showed varying degrees of positive correlation between drought severity and observation density across all study areas. In general, observation density tended to be more correlated with drought severity in urbanity than in rurality. The results of this study confirm existing small-scale ornithological sampling for drought influence on barn swallow populations. This paper seeks to explore the difficulties for integration of citizen science data into applied geographic thought and the utilizations within the field.
Natural Resources are not organized by political boundaries. Problems arise when attempting to construct a geospatial data base for analysis when rivers run through more than one state. Differences in sampling regimes, attribute criteria, and data access can lead to analysis that does not reflect the best representations of reality. This presentation discusses the data challenges encountered in preparing a Pennsylvania Department of Conservation and Natural Resources (PA DCNR) River Conservation Plan for the Youghiogheny River. The “Yough” flows north, beginning in Maryland, passing through West Virginia, and emptying into the Monongahela River in Pennsylvania. Best Management Practices (BMPs) developed for this plan will be discussed that include: attempting normalization of data across state boundaries, schema development for shared attributes, and navigating different National Spatial Data Infrastructure (NSDI) portals to meet project completion.
Disaster movies provided an attractive viewing experience beginning in the early 1900s. Several disaster movies were produced from 1910-1930 and 1950-1970 before the market saturated during what is considered the golden age of disaster movies, the 1970s. A social scientific study of 1970s disaster movies was conducted with results published in a 1980 article entitled “The Study of Disaster Movies: Research
Problems, Findings, and Implications.” The study noted the importance of popular culture in affecting people’s beliefs and discussed the roles movies play in shaping the conceptions and ideas held by the public about the physical and human features of disastrous events. It also illustrated the major substantive observations and impressions (clichés) derived from the content of the disaster movies studied. This research conducts a similar social scientific study of natural disaster movies during what can be considered the second golden age of disaster movies, the late 1990s-early 2000s. How have the major substantive observations and impressions (clichés) illustrated in natural disaster movies changed since the 1970s, if at all?
Bangladesh has been ranked seventh as the most affected by climate change since 1995 (The Global Climate Risk Index 2020). The urban population was 30% in 532 urban centres (2001), which is likely to be 50 million by 2021 and may exceed 60 million by 2031 (CUS 2008, Bangladesh Urban Forum, 2011). According to an estimate, by 2020, nearly every other man, woman and child will live in an urban area (World Bank ed., Bangladesh 2020). Mymensingh is one of the largest cities in Bangladesh with an area of 91.315 square kilometres and 471,858 inhabitants it is along the bank of the river Brahmaputra, and this makes it prone to flooding. Furthermore, Mymensingh has been identified as an area which has a high risk of experiencing earthquakes of about 7 Richter scale. Keep all this in mind, to promote resilience, the NGO Forum for Public Health and Oxfam Bangladesh have started implementing an urban resilience project in Mymensingh since from 2017 in terms of Resilience aspects i.e. Physical, Social, Economic, Institutional, and Natural.
The project adopted the approach of empowering the community in disaster preparedness and response through Community Based Disaster Preparedness (CBDP) for Disaster Risk Reduction (DRR) while working in collaboration with city authorities and local Disaster Management Committees (DMC). The collaborative governance approach has been implemented and has been strengthening civil society actors in both formal and informal urban structures and also ensuring their participation is considered as a central concept in urban governance and development.
Inclusive engagement of public, private and communities have been considered the implementation which has been contributing the sustainable change toward resilience. Coordinated efforts have been enhancing the ability to take adaptive action as well as mitigation measures against climatic and disaster risk. The project has integrated among the vulnerable urban communities, particularly women, youth, and people with disabilities in Mymensingh to become more resilient to social, economic and climate shocks and stresses.
Dollar stores have quickly become a ubiquitous feature of the American landscape. At present there are more than 41 thousand stores associated with the three major chains and a dollar store for every eight thousand Americans, with striking geographical variations at the state level. There are three thousand people per store in Mississippi but fifty thousand per store in Washington State. The distribution of dollar stores on the state level is associated with factors such as income and distance from the headquarters of the chains. Most Americans enjoy easy access to dollar stores, and some are faced with few if any shopping alternatives. The ‘dollar store debate’ focuses on the proclivity of the chains to favor low-income settings, notably in inner city food desserts. ILSR for example has mapped the correlation between race and dollar store incidence in four cities. To date, there has been little formal analysis of dollar store locational strategies. My paper combines a regression-based analysis of dollar store incidence at the state level with a focused micro-scale analysis of dollar stores’ locations in three regional settings. These are Western New York, West Virginia, and Northwestern Nebraska. Contextual circumstances of dollar stores are assessed in detail through a focus on rural Western New York. Questions of competition, uncertainty in locational strategy, and threshold population can be addressed at this local scale.
Urban trees within our cities and towns form the green infrastructure on which urban residents depend. As our population continues to grow, smart and data-driven decisions regarding urban forest planning and management are crucial. Urban tree mapping and surveys have been traditionally conducted manually, which is expensive and tedious. Moreover, these surveys are often limited in public space (e.g., street trees and parks), missing large portions of urban trees on private properties (e.g., backyard trees). The purpose of this research is to develop an automated approach that utilizes geospatial data and algorithms to identify and map urban trees, and subsequently measure the benefits they provide. To do this, publicly available 3DEP LiDAR data from USGS were used to map urban trees in the City of West Lafayette, Indiana. Building upon a tree canopy height model that was computed through observations between first and last LiDAR returns, a raster layer of tree and ground points was generated and normalized. Then, the normalized raster layer was segmented to identify individual trees by applying a means-shift clustering algorithm. Finally, key biometrics such as tree height and crown area were calculated. Ecological benefits of individual trees can then be estimated based on existing biometric equations. The proposed work has the potential for automated accurate mapping and measurement of urban trees to enhance their management allowing greater ecosystem services.
Turkey’s Southeastern Anatolia (GAP) Project aims to inspire economic growth in an underdeveloped region of Turkey through the construction of 22 dams along the Tigris and Euphrates rivers. To address downstream Iraq’s protests concerning their access to water, Turkish officials publicly promised to maintain a “fair and equitable” flow of water into Iraq. However, struggling Iraqi farmers now blame Turkey’s new dams for exacerbating the effects of drought and climate change. In an attempt to address the gap in research concerning the actual impact of Turkish dams on downstream Iraq, this project quantifies changing reservoir water levels, vegetation levels, and population levels surrounding the upstream Turkish dams and the downstream Iraqi Mosul Dam. Using NDVI data to estimate changing vegetation over time, UN-adjusted population rasters to estimate population change, and satellite radar altimetry to estimate the changing water levels of the dam, we assess whether Turkey’s agricultural development seems to come at the expense of Iraqi farmland and farmers.
Climate change is causing many significant shifts throughout the world’s ecosystems, including those in oceans. Oceans act as a buffer to climate change but are reaching their tipping point for absorbing an immense amounts of heat and carbon dioxide. Rising ocean temperatures are causing many organisms to relocate to more suitable locations beyond their traditional zones. Great White Sharks, Carcharodon carcharias are one such species whose locations are actively shifting. Historically they have been found along the coasts of every continent except Antarctica, existing mostly along continental shelves and open waters of temperate and subtropical waters with a temperature range 50-80°F. The expansion of their range poleward, seems to be the result of following their food sources. This migration is seen also in the shifting locations of Shark nurseries. This presentation discusses the locational shifts of the Great White Sharks along the California coast line. Tracking and understanding these changes is important for the protection of the species, understanding the locational expectations of creditor prey expectations, as well as the safety, perceptions and education of the public who recreate in coastal waters.
On February 3rd, 2023, a Norfolk Southern freight train derailed in East Palestine, Ohio, about a quarter mile west of the Ohio-Pennsylvania state line. According to the Ohio Environmental Protection Agency (EPA) about 20 of the cars effected by the derailment contained hazardous materials including vinyl chloride, ethylene glycol, ethylhexyl acrylate, butyl acrylate and isobutylene. Some of these cars caught fire, while others spilled into a ditch that empties into Sulfur Run. Sulfur Run joins Leslie Run, which empties into the Ohio River. This paper seeks to analyze field samples taken from both Leslie and Sulfur Run to determine current macroinvertebrate diversity and water quality. Furthermore, it will compare current findings with studies pre-derailment to determine if there has been any potential impact on the health of the streams as a result of the spill. Sampling was performed based on SERAS standard operating procedures (SOP) 2054 for benthic macroinvertebrate sampling using vSURBER net procedure.
Abstract
The Enabling Crop Analytics at Scale (ECAAS) project aims to produce open-access agricultural maps and ground truth data to enhance the delivery of farm extension services. It creates high-resolution maps of the various crop types and the potential yields relating to them using this data. These maps are used to identify potential production improvement areas and provide farmers with more accurate information. The project uses satellite imagery and ground-based data to monitor crops.
By creating accurate and up-to-date maps of agricultural land, farmers can learn more about their lands and the resources they have available to them. Ground truth data, such as crop yields and soil types, are also used to better understand farmers' preferences and determine how to best meet those needs. Farm extension services may be customized to the specific needs of individual farmers using open-access agricultural maps and ground truth data. High-resolution maps that emphasize areas with the potential for improved agricultural production are created using a complete approach that combines drone technology, remote sensing, and GIS.
Ground truth data is also essential to provide reliable information on the land and its resources. It enhances our understanding of the existing state of the land and its resources, enabling the development of more beneficial farm extension services. The generation of open-access agricultural maps and the acquisition of real-world data allow farmers to obtain more precise and efficient farm extension services.
Keywords: Open-access agricultural maps, ground truth data, extension services
Food access varies widely depending upon the neighborhood of residence. For some neighborhoods, a designation of a food desert has been documented. Food deserts are neighborhoods that have limited access to healthy and affordable foods in the form of supermarkets or grocery stores. The United States Department of Agriculture began to produce a food desert atlas that designated tracts with this limited access to healthy food. However, their criteria for healthy food is restrictive to only large stores. This research documented a more thorough examination of food access in the low-income, low-access food desert tracts in the St. Louis MSA. The result showed fewer food desert tracts than was initially provided by the USDA. By including smaller food stores and more local options, food access is found to be much better than what was suggested by this federal agency. Additionally, healthy food was plentiful for some low-income, low-access tracts due to a diverse offering of fast-food options and sit-down restaurants. For others, the inability to access high-quality nutritious food was apparent. A variety of mapping techniques is utilized to showcase these discrepancies.
What is a commercial strip? Is it necessarily motor-vehicle based? What underscores strips' emergence and development, and since when? Are all strips essentially alike, sharing the same initial circumstances? If not, how do those circumstances differ, and do differing strip types arise from different initial contexts? I see little evidence that these questions have been systematically addressed since Jakle and Mattson's seminal work on the Urbana-Champaign strip. And I think that, forgivably, their case study served to narrow our grasp of the sheer variety of strips' initial circumstances and subsequent development. In this presentation I hope to remedy these lacunae and encourage further research focused on this important element of the American commercial roadside.
The need for proactive and sustainable strategies is paramount in the ever-evolving landscape of climate change and its profound impact on businesses worldwide. Our presentation highlights the critical significance of location data in developing practical solutions for ensuring business continuity using the Area Business Continuity Management (A-BCM) framework, particularly in the context of climate-related risks. Furthermore, we demonstrate how industry-specific location data can influence the five crucial steps within the A-BCM framework (Sapapthai et al., 2020).
We will delve into the untapped potential of location data, emphasizing its critical contribution to A-BCM by providing a comprehensive understanding of how environmental shifts affect specific business locations. A-BCM assumes a central role in protecting business operations from disasters. This proactive approach safeguards businesses, contributes to job retention, and mitigates adverse socioeconomic consequences (Kato & Charoenrat, 2018). We illustrate how organizations can identify vulnerabilities and formulate robust continuity strategies by integrating environmental factors with industry-specific parameters.
Based on the work of Baba et al. (2014), our research demonstrates the transformative potential of location data in empowering businesses to make well-informed decisions and establish resilient strategies. We emphasize the crucial significance of A-BCM in fostering long-term sustainability for businesses facing increasing climate-related
Abstract
Historical appraisal of gasoline stations has previously been limited primarily to their growing association with Big Oil in the twentieth century. Research emphasis has included: branding, architecture, place-product packaging, and the attrition of small independent operators, a withering which reached a crescendo in the 1970s. The middle ground of multiple station independent ownership in regional or metropolitan settings remains largely unexplored. Based on oral sources, this paper traces the emergence and growth of a 134 - station 'empire' of independent discount retail gasoline stations in Buffalo/Niagara Falls. Now in their late 80s, Harold Geiger and his wife Patricia bought their first Buffalo, NY gasoline station in 1967. Creative financing added three dozen stations within a decade. Thereafter, rapid expansion relied on cheap but not "Big" oil imported from Montreal. The Geiger-owned stations achieved recognition without branding, without distinctive architecture or signage, with canny location choices, impressive price competition, early adoption of self-service, and even with a foretaste of the minimart revolution. However, their near-ascendancy in the 1970s could not survive an oil crisis.
As renewable energy development continues to grow within the U.S., it brings with it its own opportunities and challenges. In particular, there are concerns about the local environmental impacts that communities will experience at the expense of a national reduction in greenhouse gas emissions. This research focuses on the environmental planning and permitting of renewable energy projects to understand the current challenges and opportunities that exist when siting utility-scale wind and solar projects. Within the realm of environmental planning, the role of environmental non-profits has become more prominent. The literature identifies multiple ways in which environmental non-profits can contribute to the regulatory process, including: 1) being deeply embedded in the normative process that encourages compliance via public pressure; 2) contributing to the ways in which regulations are enforced; and 3) contributing research or other material as a third party to foster social learning within environmental regulations. The goal of this research is to understand the role that environmental non-profits play in the siting and planning of renewable energy development in the Wind Belt states. I conducted interviews with 16 environmental non-profit employees working for national organizations (either in the national office or for state chapters) as well as state and local organizations. For this presentation, I will be presenting the preliminary results of my qualitative analysis. I will highlight the themes identified from my interview transcripts, including the challenges non-profits currently face and the benefits they feel their organization could provide to future planning of renewable energy projects.
A primary goal of working landscape conservation is to protect large blocks of farmland. This pattern supports the long term interests of farmers and farm support industries. There are a variety of metrics a community could use to track success in this area, with dollars spent and acres preserved among the most common. Less common, but particularly important for communities like Lancaster County, Pennsylvania which have active and mature farmland preservation programs, is the configuration of preserved land.
This study uses GIS and the raster analysis application Fragstats to examine the configuration of preserved farmland in Lancaster County over time with a focus on farmland cluster size, shape, and connectivity. It also examines the location of preserved farmland with respect to desirable locations such as urban growth boundary edges and agricultural zones. The paper concludes by highlighting and explaining key gaps in the county’s network of preserved farmland and providing recommendations for communities interested in enhancing the connectivity of their preserved land.
About 12,000 years ago(Ice Age), the climate of south-central plains of America alternately experienced wet and dry periods. The region later transformed itself into a desert plain grassland. Currently, the region is undergoing another megadrought that is predicted to last for centuries in future. From the lens of hydrological and meteorological drought conditions, these prolonged and extreme environmental events may have irreversible and adverse impacts on a perennial river system like Canadian river. Originating from the Sangre de Cristo Mountains along the Colorado-New Mexico border, the river travels eastward across many different climate regions, ecoregions, and cultural regions before emptying into the Arkansas River, later draining into the mighty Mississippi river. The river is dammed and diverted throughout the basin for multiple purposes: irrigation, recreation, industrial, municipal, and energy extraction. This situation has given rise to socio - economic drought conditions across the entire watershed. In addition, the river basin plays an increasing role in the region’s energy needs, which is connected to its water sustainability. The interconnectedness between drought conditions, water quantity, population variability, and climate change complexities cannot be described by the simplistic explanation of cause and effect. These systems will reinforce one other through dynamic and multiple feedback mechanisms within factors ranging from irregularity in rainfall patterns to socio -economic conditions. The study aims to predict the connections between these factors of influence and the different types of droughts, both individually and in conjunction with one another, to foresee the faith of the river over time and space.
The Binghamton University Nature Preserve spans 190 acres of land, with a notable 20-acre wetland, and is a multifaceted space with several missions. It is dedicated to preserving the ecological integrity of this landscape, fostering biodiversity, and facilitating research and environmental education. Furthermore, it serves as a recreational space for students, athletes, and community members, enhancing the bonds between the campus and the neighboring community. This research focuses on Binghamton University Nature Preserve as a case study to explore the intricate balance between two vital objectives: ensuring equal access for all user demographics, while safeguarding the ecosystem services it provides. To achieve these objectives, the study employs a diverse array of public engagement methods, encompassing surveys and community mapping, to gather valuable insights from diverse stakeholders. Additionally, the research integrates cutting-edge technology, such as drones and remote-controlled vehicles equipped with iPhone LiDAR sensors to acquire comprehensive data on trail conditions and the surrounding environment. The innovative fusion of community input and high-tech data collection empowers a data-driven approach to environmental management, offering the potential to advance accessibility and sustainability simultaneously. By bridging the gap between these two fundamental considerations, this study not only enhances the Binghamton University nature preserve, but also paves the way for the formulation of inclusive and environmentally responsible public policies, potentially transforming the management of natural preserves nationwide.
Many times local governments, are tasked to look at changes in employment patterns over a specific time period at a localized level , often where a comparative analysis is required. A Shift-share Analysis measures the movement (shift) of the local economy into faster or slower growth sectors and the community’s larger or smaller portion (share) of the growth occurring in a given economic sector at the state or national level. This analysis can help identify industries where a regional economy has competitive advantages over the larger economy. A Shift-share analysis takes the change over time of an economic variable, such as employment, within industries of a regional economy, and divides that change into various components. Historically, a Shift-share Analysis of local employment has been done at the county or MSA levels, as that has been the most granular level of geography that annualized employment data by industry sector has been made available via Federal data sets such as the Bureau of Economic Analysis. This paper looks at how to complete a Shift-share analysis and Industry Cluster (Location Quotient) at the local level using ACS (American Community Survey), 2-digit industry NAICS employment data for the communities of Albany, Corvallis, and Lebanon Oregon between the years of 2019 and 2022.
While there's a clear trend towards the widespread collection and storage of data, there is still uncertainty around the precise impact that Spatial Big Data has had within the retail sector. Spatial Big Data provides a wealth of interconnected spatio-temporal data, enhancing our understanding of consumer behavior with greater sophistication. As the industry increasingly moves towards data-driven decision-making, organizations face growing pressure to incorporate data into their planning processes. This paper presents findings from semi-structured interviews with 10 senior managers responsible for retail location decision-making in leading Canadian firms. The study highlights the transformative effects of data and analytics, while identifying the tools, techniques, and data used to reinforce decisions regarding retail locations. Furthermore, the study highlights the potential benefits and challenges of adopting Spatial Big Data Analytics.
Business geographers devote considerable effort to develop models of space to answer complex spatial questions. Unfortunately, little thought is given to the accuracy of the input data in most of these models. This paper examines the accuracy of tract level population and income data reported for the second quarter of 2020 from five spatial-demographic data vendors (Experian, Synergos/PopStats, ScanUS, ESRI and EASI) by comparing their estimates to the 2020 Census enumeration of population as well as the American Community Survey (ACS) 5-year estimates of income. Data are compiled for 80 Census tracts in the 40 fastest growing US metropolitan areas. These results are compared against an identical 2015 study. Mean absolute percent errors (MAPE) for 2020 population estimates were found to have increased marginally since 2015 and median household income estimations were consistent with the measured accuracy in 2025. A significant spatial variation in the magnitude of these errors was also found, with MAPE increases being the most substantial in urban tracts. The magnitude of this bias grew after controlling for the size of tracts, errors increased substantially with urban tracts. The consistency of the errors and biases found in these vendor data likely result in flawed location analysis, particularly in rapidly growing in-town neighborhoods.
Scholarly interest in mapping and GIS is both increasing and broadening. Coming from a university with solid traditions in cartography and GIS, I was interested to observe what the situation was at the University of Pittsburgh when I accepted a position there two years ago. As seen from two documents produced by the University Library System, the importance of these trends was recognized in the annual fiscal year plan by chartering in 2016 a project team to produce a report with recommendations for the development of spatial services in order to promote the ULS' role as a campus hub for geospatial data activity and expertise.
In the proposed presentation, I will explore and review the main strategic areas identified by the project team, and some specific actions I undertook based on the report’s recommendations.
I will also describe several faculty projects that needed extensive cartographic assistance, most notably the interactive map I created for the Mapping Religious Pittsburgh project and original maps created for a published article and a book by Patrick Manning, Past President of the American Historical Association, as well as a map portal for an online database of Chinese village gazetteer and several more.
The genesis of “Powerful Geography”—a new concept in teaching and learning—began in the 1980s, during the building of the Applied Geography program in the Department of Geography and Environmental Studies at Texas State University. This presentation discusses the evolution, relevance and importance of the concept of “Powerful Geography,” emanating from five distinct time periods: Period 1 revisits the geo-history of applied geography at Texas State and our creation of the Masters of Applied Geography program and degree; Period 2 surveys a host of counseling and career opportunities offered by the American Association of Geographers (AAG); Period 3 presents the underlying concepts of “Powerful Geography” which include Geo-capabilities and Powerful Disciplinary Knowledge, developed by European geographers and now deeply set in European schools and academic universities; Period 4 surveys the efforts of geography education researchers from the Gilbert M. Grosvenor Center for Geographic Education who have worked to develop the teaching methods of “Powerful Geography” for U.S. schools, and universities. Finally, Period 5, the Present, asks: Where do we go from here? What are the responsibilities of geography professional education institutions? What are the support needs from school districts and state Boards of Education? The ultimate aim of this paper is to increase awareness of this new “bottom-up” approach to teaching geography which enhances students’ understanding of the importance and relevance of geography to their everyday lives, as well as the application of geography in their future careers.
What does the future hold for science and the field of geography more specifically? And how might that future better connect with society? While the answers to these questions are quite complex, here, we will discuss how community geography partnerships can drive support for the next generation of science. Public and private partnerships in learning and research are increasingly important, particularly with the increased recognition that the solutions for society’s greatest challenges and opportunities require thinking, creativity, and imagination across multiple fields and multiple voices. In our time together, we will explore the ways in which Citizen Science GIS and GeoBus at University of Central Florida support shared geospatial technology learning experiences for community partners, college students, K-12 educators, and K-12 students across the globe through a unique partnership approach to community geography. Citizen Science GIS is an international organization that aims to make geospatial technologies for science more accessible and understandable by fostering relationships between communities and scientists, of all ages, across the globe. In this presentation, we’ll consider the ways in which our partnership-centered work supports the next generation of science and provides great societal impact as an example of applied geography.
This presentation is part of my Geography and Science Education series: “Meteorology and Myth”. Red Sprites, Elves, and Pixies are types of Transient Luminous Events (TLEs). SPRITE stands for Stratospheric/Mesospheric Perturbations Resulting from Intense Thunderstorm Electrification. These ephemeral bursts of electricity in the upper atmosphere were previously thought of as being inconsequential for an understanding of daily weather. Recent research on upper air electricity suggests that TLEs have some impact on surface weather, atmospheric composition, and our ozone layer. TLEs may influence high-altitude aircraft, balloons, and low orbit spacecraft. They have contributed to variations in atmospheric chemistry, which may influence climate change. There is still significant educational and research potential about TLEs. The purpose of this educational project is to stimulate interest in sprites and other TLEs in the context of weather education. Evocative stories combined with striking imagery may entice student interest in the upper atmosphere. This project includes a literature review of the recent understandings of TLEs, and concise generalizations derived from current research. Outcomes are lesson plans for instructors; this includes handouts, weblinks and video playlists. Reference materials for practical classroom use are included.
Keywords: upper air meteorology, sprites, lightning
Protests erupted in Rochester, NY in September, 2020, following the death of Daniel Prude, a Black man who died after being restrained by Rochester police. Video footage of the subsequent Black Lives Matter protests went viral, making national and international news. This presentation maps the video footage created by one Rochester based journalist that went viral for all the wrong reasons: it was used as part of a disinformation campaign. A web GIS map developed from R-based analysis of Twitter data and ArcGIS Online illustrates the international distribution of one Tweet as ‘fake news’ and maps just how far and wide it can spread. This analysis forms one layer of a ‘deep map’ examining the history of race in the City of Rochester, NY. We conclude with discussion of the interrelationships between roots of segregation, current demographics, and uses of social media in the context of protest
For the majority, our experience of landscape is driven by the visual. While we often use visibility models built into geospatial software to capture viewsheds, these only represent portions of the landscape that can be seen and do not take into account other environmental and physiological aspects that limit what we can perceive. In 1975, landscape architect Tadahiko Higuchi offered a set of indices that build on the traditional viewsheds by considering variables such visual clarity, atmospheric moisture, and others to capture the nuance that is missing from the traditional visibility models. Moving from what is visible to what is perceived has provided greater insight over the last half century as the approach has been used across Geography, archaeology, and other fields. This presentation will focus on the application of Higuchi’s indices and related considerations of visual perception along a portion of the Shikoku Buddhist Pilgrimage in Japan.
This poster will focus on the development of an immersive virtual landscape platform for the exploration of local stories and knowledge documented as part of the Gullah Geechee Digital Project. This project, led by the Athenaeum Press at Coastal Carolina University, brings together South Carolina Gullah Geechee archival collections held by a number of national and regional partners for the express purpose of creating online digital access to these valuable materials. This portion of the project focuses on Sandy Island/Murrells Inlet, Plantersville, Johns Island, and St. Helena Island. The project’s goals are twofold: create digital access to these collections and develop interpretation of these materials for access by communities and the general public. This second goal is the driving force behind the development of our immersive virtual landscape platform.
To date, three applications have been designed and prototyped: Virtual Sandy Island, Virtual Plantersville, and Virtual Johns Island. A fourth prototype, Virtual St. Helena Island, is under early development. Each of these applications has been developed using the Unity Real-Time Development Platform, and centers around a 3D virtual landscape recreation that users can explore with a third-person character perspective. Embedded within this landscape are spatial narrative elements in the form of multimedia, such as text, images, and video. These story elements enhance a user’s explorative experience with the historical, archaeological, ethnographic, and other scholarly information that guide our knowledge of the past and current cultural landscapes of the Gullah Geechee people.
What impact does the history of redlining have on forest composition in neighborhoods of cities in upstate New York State? The practice of redlining, or discriminatory lending practices, as evidenced by the 1930’s era Homeowners Owners Loan Corporation (HOLC) maps is well known to have affected neighborhood property values. The web GIS tools from the Mapping Inequality: Redlining in New Deal America project are integrated with urban forestry data sources here to examine potential linkages between the legacy of ‘redlined’ properties and their forest composition. These data are scanned images of the HOLC maps in web GIS data format (e.g., GeoJSON) for direct placement into web GIS applications. Spatial analysis of current property values and percent tree canopy cover for nine neighborhoods in Syracuse, NY was conducted with results indicating a substantial difference in tree canopy cover and property value. Spatial analysis of percent tree canopy cover was also conducted for the Boroughs of Manhattan, Brooklyn, and Queens in New York City. Results indicate limited differences were found in median tree canopy cover among neighborhoods in Manhattan but significant differences among neighborhoods in Brooklyn and Queens. This project adds additional insight into the value of urban tree canopy cover as an indicator of inequalities in property values, home ownership rates, and in resilience to climate change.
Toronto is Canada’s largest urban market. Located on the shoreline of Lake Ontario, the city has an extensive waterfront that has transformed from industrial to mixed-use over recent decades. Beyond converting the Toronto skyline, the redevelopment of Toronto’s Waterfront has resulted in a marked increase in employment and residential population. Various forms and functions of retail and service activities are integrated within many of the redevelopment projects. This paper provides case-study based insights into recently completed, under-construction and planned development projects in the Toronto Waterfront area. The rapid transformation of Toronto’s Waterfront raises many questions about integrating retail within mixed-use developments. From a market perspective, questions primarily relate to ensuring that retail meets the needs of the various consumer groups that form the marketplace, along with structural questions related to the future needs for physical retail space. At a societal level, and given the significance of the Waterfront in defining the vista of the city, there are many questions about inclusivity, equity and the public realm and how the Waterfront more broadly serves the city and its citizens. The paper highlights the critical role of an applied geographic lens in triangulating multiple perspectives on urban change and commercial activity.
The shopping centre industry is undergoing a rapid transformation, with many centres showing evidence of redevelopment to other land-use types. The types of redevelopment range from complete transformations to non-commercial use, complete redevelopment to mixed-use that includes new retail construction, to pad densification and anchor space redevelopment. These emerging redevelopment patterns have primarily been triggered by increasing pressures of urbanization, changing consumption preferences due to demographic change, and many years of declining shopping centre productivity that has commonly been blamed on competition from large format power centres at the urban periphery and the effects of growing E-commerce penetration. Considering that many industry experts do not forecast a significant decline in demand per capita for commercial space, the speed and justification for shopping centre redevelopment are concerning and should be investigated further. This paper investigates the nature and extent of major shopping centre redevelopment activity in Canada. The analysis includes a breakdown of redevelopment activity by shopping centre type and geography. The paper explores the implications of shopping centre redevelopment from a retail demand-supply and commercial real estate perspective.
In 2022, a citizen-sponsored initiative to substantially increase the City of Los Angeles property transfer tax for higher priced properties passed with 57% of the vote. The measure, which took effect on April 1, 2023, increased the property transfer tax from the long-standing rate of 0.45% of the property sale price to 4.0% for properties selling for between $5 million and $10 million. The tax on properties selling for more than $10 million increased to a rate of 5.5% of the sale price. The intent of the measure, known officially as Measure ULA, but often informally referred to as the “Mansion Tax” (even though it applies to all properties, including commercial and industrial buildings), is to generate money to address the city’s housing shortage and homelessness problems. This session examines transaction data within the city of Los Angeles, as well as within surrounding Los Angeles County, to provide insights regard
Going from the basic understanding of the alignment needs for multi-county/regional planning and programming and the great number of possible alignments, "A Solution to the OMB recognized Geographic Need: 'a territorially exhaustive classification that covers all of the United States and Puerto Rico,' State Determined Sub-State Districts" will be presented. The fact that each State will have to submit its districts and geocode them is applied geography work. Most States have a system. The Virginia one is an excellent model since alignment with State agencies was a design feature implemented in 1972. Regional planning in Virginia had a strategic advantage as a consequence. The use of Sub-State Districts for Economic Development was a recommended strategy of the Southern Growth Policies Board in the 1970s.
Identifying your career across the evolving professional landscape of options for the geographer can be both daunting and exciting. Geographers hold a rich set of transferable and specialized skills and knowledge that make us highly suited and adaptable in emerging and traditional work environments. Whether you are embarking on your career or are considering making a mid-career transition, this workshop sets out to help participants navigate the initial steps toward their new careers. These steps include often-overlooked self-assessment, which is key to setting and identifying meaningful career goals that allow for professional satisfaction, as well as personal and professional growth. Self-assessment tools and plan-building are designed to empower participants with knowledge and strategies to chart a successful career path. Participants will learn how to identify their strengths, values, and interests, align them with potential career paths, and create signposts to reach their objectives.
For 7 years, I have worked with our Binghamton University President, Harvey Stenger, and with our faculty and staff . Three cities in Broome County, N.Y. were selected as rust communities by NYS. Johnson City, one of three of i-Districts (Innovation Districts, particularly Main Street and certain adjacent streets), won funds from New York by Governor Cuomo -drawn from the $1 billion funds for rust belt cities in Upstate NY in 2015. Two important engines were selected for Johnson City, NY to generate new businesses and jobs, United Health System ($152 million investments) and Binghamton University (more than $100 Million investments).
President Stenger directed the University efforts and also generated significant University Division of Advancement of Division Funds (private non-University donations). He also asked me to direct Johnson City research with him (Co-Researcher). We routinely create reports on Johnson City landscape changes. Changes are monitored and analyzed through a range of data and analysis employing multiple-methods. He funded the equipment and graduates necessary to work with us.
Today, I illustrate how a President, two faculty, and 7 graduate students in my class (not all funded by the President) focused on one neighborhood in my graduate class for 16 weeks, employing advanced field work with support of data and the use of technical approaches for the analysis.
This study examines the spatial distribution pattern and socioeconomic determinants of poverty in the United States between 1990 and 2020. Drawing on data from the decennial census and American Community Survey, we use the Local Indicators of Spatial Association (LISA) statistics to analyze the detailed changes in county level poverty rate over the last three decades and identify the socioeconomic driving forces behind these spatiotemporal changes by employing spatial econometric models. Specifically, the techniques of Bivariate LISA and LISA Cluster Transitions are utilized to show how the highest and lowest values of poverty rate have been spreading over time. Both spatial lag and spatial error models are employed to identify the spatial effects of socioeconomic factors in determining the county level poverty.
The population of Chinese immigrants in the United States has undergone progressive growth in the past 50 years and has reached an epidemic number. As minorities, the Chinese immigrants move into receiving places to adapt and succeed in a new social structure while not losing their own identity. Previous studies highlight the role of local contexts that lead to an internal moving decision. Most of these studies view local contexts as global factors assumed to apply equally over a study area. However, the contextual factors do not disperse evenly across space, nor do their relationships with migration behavior. Understanding the spatial variability of factors related to Chinese people's migration in the study area is necessary. Therefore, this paper aims to explore the role in which neighborhood context may predict migration behavior, with particular attention to how migration factors and their effects vary across space.
This research presents novel applications of two methods: clustering analysis (followed by regression models) and multiscale geographically weighted regression (MGWR) to the Chinese population in the New York-Newark-Jersey City metropolitan statistical area as a case study. Wages, education, English proficiency, and self-employment status are crucial variables in differentiating movers from non-movers. Having naturalized citizenship has a dual effect on migration behavior. Among the movers, stratifications exist in the immigrant Chinese population, as each subgroup has its particular migration pattern and significant indicators. Approaches considering data associations in both geographic and non-geographic dimensions are promising.
Twenty years ago, Chester Hartman and David Robinson (2003) urged scholars to focus their attentions on the “hidden housing problem” of eviction, at the time under-studied and attended to in comparison to homeowner issues. Since, social science research on eviction has exploded, with special issues being drafted entirely around the subject (Howell and Immergluck, 2021). National databases of eviction, like the Princeton Eviction Lab, provide large levels of quantitative data, while scholar-activist endeavors, such as the Anti-Eviction Mapping Project, provide place-based, participatory research at the local level. Geographic thought has had strong influence on this research, even outside the formal bounds of the discipline, through methodological approaches, like spatial analysis and participatory methods, and theoretical applications, such as critical, urban, and feminist thought. This paper has two aims. First, I will evaluate the ways in which geographic thought has been applied to scholarship and activism on eviction and contributed to the understanding and prevention of displacement. Secondly, I will present a case study of community-engaged analysis in Syracuse, New York as one example of eviction research through a geographic lens.
Hartman, C., & Robinson, D. (2003). Evictions: The hidden housing
problem. Housing Policy Debate, 14(4), 461–501. https://doi.org/10.1080/10511482.2003.9521483
Howell, K., & Immergluck, D. W. (2021). Evictions: Shedding Light on the Hidden Housing Problem. Housing Policy Debate, 31(3–5), 374–376. https://doi.org/10.1080/10511482.2021.1929342
This presentation showcases a successful collaboration between two professors in Urban Sustainability and Data Visualization. They designed a cross-course exercise centered on the UN's Sustainable Development Goal 11 - "Sustainable Cities and Communities." This innovative approach aimed to leverage the strengths of both disciplines for a comprehensive analysis of Pittsburgh's sustainable profile related to Goal 11 and its ten targets. Students from both classes were strategically paired, with Data Visualization students transforming complex data into insightful visual interpretations and Urban Sustainability students focusing on research and analysis. This collaboration examined ten specific targets under Goal 11, from affordable housing to disaster resilience. The result was an updated profile of Pittsburgh's Urban Sustainability, highlighting its progress toward SDG targets. This interdisciplinary endeavor provided students with a profound understanding of sustainable urban development's complexity and emphasized teamwork and diverse expertise. By combining data visualization and urban sustainability, this exercise exemplifies pedagogical innovation, encouraging holistic problem-solving and real-world application. The presentation will highlight key findings, innovative methodologies, and their impact on student learning outcomes. It will also emphasize the broader applicability of this collaborative approach in other urban contexts, promoting positive change aligned with the Sustainable Development Goals.
For decades, geographers have acknowledged the potential of artificial intelligence (AI) to inform geographical problem solving (Couclelis, 1986; Openshaw & Openshaw, 1997; Smith, 1984). More recent applications have demonstrated the ability of AI to assist in analyzing remote sensing, GIS, and other geographic data (Hu, 2018; Janowicz, et al., 2019). The advent of generative AI feels different, however, as programs like ChatGPT, Bard, DALL-E, and others have increased the accessibility of AI and have broadened the application thereof to all aspects of the geography workplace. Therefore, discussion is needed to develop expectations, guidelines, and best practices for the use of generative AI by applied geographers. Alignment of best practices in academia, government, and industry is necessary for proper training, expectations, and the health of the discipline. Come share your experiences and thoughts and help applied geographers be at the forefront of this global issue.
References:
Couclelis, H. (1986). Artificial intelligence in geography: Conjectures on the shape of things to come. The Professional Geographer, 38(1), 1-11.
Hu, Y. (2018). Geo‐text data and data‐driven geospatial semantics. Geography Compass, 12(11), 10.1111/gec3.12404
Janowicz, K., Gao, S., McKenzie, G., Hu, Y., & Bhaduri, B. (2020). GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond. International Journal of Geographical Information Science, 34(4), 625-636.
Openshaw, S., & Openshaw, C. (1997). Artificial Intelligence in Geography. John Wiley & Sons, Inc.
Smith, T. R. (1984). Artificial intelligence and its applicability to geographical problem solving. The Professional Geographer, 36(2), 147-158.
This presentation examines the variability in horizontal accuracy results in the photogrammetric processing and production of orthophotos from mosaiced drone-acquired aerial photographs, comparing imagery processed with ground control, without ground control, and onboard real-time kinematic (RTK) global navigation satellite system (GNSS) position derivation. The implementation of ground control points (GCPs) in photogrammetric processing of drone imagery establishes a link between the image coordinate system of the aerial photographs collected in flight, and ground coordinates in the rectification of images in the production of orthophotographs that is supposed to significantly improve the global horizontal and vertical accuracy of resulting maps. Implementation of the real-time kinematic method requires an unmanned aircraft designed to allow the utilization of additional GNSS receiver hardware (involving additional expense), but theoretically obviates the need for ground control through the high accuracy of position calculation of the onboard GNSS receiver on the drone in flight. This pilot study will provide evidence regarding the comparative horizontal accuracy in the production of orthophotos derived from the above methods, and aid in decision-making regarding methodologies required to obtain near survey-grade results from drone-based photogrammetry.
The temporal dimension of geographic data is often ignored such that outcomes from analysis of geographic objects or events are often misleading. Researchers often apply spatial analysis to identify hot/cold spots of geographic events, such as crime or diseases occurrences. However, hot/cold spots do not remain constant over time. There may be hot/cold spots that are just emerging or slowly diminishing. Alternatively, hot/cold spots may be stubborn through time, or some locations may never be hot/cold spots of the events.
As the importance of temporal dimension embedded in geographic data slowly gaining attention, a number of quantitative methods have been developed for finding spatiotemporal clusters of geographic objects or events.
This presentation will highlight some of these newly developed methods and their possible applications.
Vague places are places that lack a certain and unambiguous boundary to their spatial regions. People's perception of vague places' spatial extent is often subjective and is based on their experience and understanding of the geographic context. Such subjective understandings of places might cause ambiguities and inefficiencies when communicating and sharing geographic information, especially between human and computational systems. This paper aims to 1) model the vague place of Western New York (WNY) using social media data and 2) understand the vagueness associated with such places from an ontological perspective. Social media (e.g., Twitter/X) users' posts were acquired to investigate people's perceptions of the spatial extent of WNY. The eastern boundary of the WNY region is then modeled using spatial clustering algorithms (e.g., DBSCAN) and compared with various present institutional definitions of the WNY region and with the historical delineation of the region. The result shows that WNY's eastern boundary moved eastward compared to its original location when the state acquired the region. Some current definitions of WNY (e.g., from social and governmental agencies) need revision to be more consistent with the general public's understanding of the space. Lastly, the vagueness associated with places such as WNY is discussed and addressed in the context of Basic Formal Ontology (BFO) to bring insights into the issue from a philosophical perspective.
The COVID-19 pandemic has created significant challenges for human mobility behavior worldwide. We investigated how to measure the resilience of human mobility behavior in 130 countries and regions based on multi-scale from February 15th to August 15th 2020 and from January 1st to June 30th 2021. The study demonstrates that: (1) On global scale, human mobility showed a significant decrease in the reaction period, and residential category accordingly was on the rise. However, in adaptation period, except for the behavior change of the residential category, the mobility of remaining five categories is on the rise in the adaptation period, especially in the increasing mobility of parks; (2) As for the regional scale, all the continents experienced sharp declines and fluctuations in the reaction period. However, the daily FI dynamic variations of human mobility behavior in Africa were more stable than others in adaptation period, and Asia is characterized by relatively low stability, with several sharp declines during the study period; (3) On the analysis of national level, different countries and regions have significant differences in the adaptation to the changes in human mobility behavior. 130 countries and regions were divided into five categories of resilience. This research aims to provide reference for formulating policies to deal with future unpredictable events.
Invasive pests have long been recognized for the various threats they pose to natural ecosystems and the major economic damages they cause. If invasive pests left unchecked, it can result in a reduction in natural biodiversity, harm to specific populations, and a loss of overall ecosystem function from local to regional scales. Public awareness is the key for the prevention, early detection, eradication, and/or mitigation of invasive pests. Here, we introduce Alien Forest Pest Explorer (AFPE), an interactive web-based ArcGIS dashboard to engage and educate the general public, as well as natural resource managers. AFPE provides detailed spatial data describing pest distributions and host inventory estimates for damaging, nonnative forest insects and pathogens currently established in the United States. To date, the AFPE database includes 74 species of forest insects and 15 species of forest pathogens. It provides (1) national distribution for each of the invasive pest and (2) their corresponding damage and invasion risks at any user-defined geospatial scales within the continental U.S. Our AFPE dashboard can also be embedded by any web-services hosted by private organizations and public agencies to facilitate the knowledge disseminations and raise the awareness of the most damaging pests to our forest ecosystems.
Neighborhoods in small and medium sized legacy cities often struggle to deal with a vast array of problems, including vacant land. Top-down approaches to managing vacant land, including aggressive enforcement campaigns against tax delinquent property owners, and more recently, the creation of land banks, have largely failed to help local communities. Vacant land management strategies implemented at the neighbourhood level offer more hope, specifically if local organizations and residents feel vested in implementing those strategies. For many communities, a first step in managing vacant land is answering a simple question, how much vacant land is there in a community? A lack of access to data, maps and software, combined with a lack of expertise often make answering basic questions like this problematic. These challenges can sometimes be overcome through partnerships with other communities, non-profit organisations and local academic institutions.
In summer 2022, students from Youngstown State University and the University of Pittsburgh began partnering with residents and community activists from the Borough of Swissvale, Pennsylvania to map and describe vacant lots using a citizen- and environmental- centered approach. Participants in this roundtable will discuss the success and challenges of project/ community-based learning in general, offer insights from the faculty, students and Swissvale community members involved in the vacant land mapping project, while seeking input from other students, faculty and community members involved in community-based learning.
This panel session investigates how the fields of economic geography, regional economics and regional science have evolved, changed, and intersected over time, and where synergies exist moving forward. More importantly, is the role “location” has taken in recent years, as regional economic data (sub state level) has become more readily available. We are also now seeing more powerful analytical tools available within the GIS suite. How has this impacted the work and research questions being asked by these disciplines. Where can there be more cross-collaboration between geographers and economists, especially with economic development opportunities of “distressed” communities and regions, both urban and rural? What are some of the challenges these fields have encountered within the current regional economic landscape, including data availability and timeliness of data? What if any, are changes that need to occur within these disciplines to remain relevant and in the forefront of both research and meeting community needs?
As digital technology produces a culture of accessibility to modern day maps and digital data, this this panel explores the state of Map Libraries in Public institutions, how they may be changing, how they should or could change and why they are still important. An open discussion is invited from the audience.
Understanding the processes and mechanisms of the spatial spread of epidemics is essential for making reasonable judgments on its development trends and for adopting effective containment measures. Using multi-agent network technology and big data on population migration, this research constructed a city-based epidemic and mobility model (CEMM) to stimulate the spatiotemporal of COVID-19. Compared with traditional models, the CEMM model is developed from an urban network perspective and emphasizes the important role of intercity population mobility and high-speed transportation networks. Through scenario simulation, this study also quantitatively evaluated the effect of such control measures as “city lockdown” and “decreasing population mobility” on containing the spatial spread of the COVID-19 epidemic in China.
When used as directed, pre-exposure prophylaxis (PrEP) lowers the risk of contracting the human immunodeficiency virus (HIV). Improving access to PrEP is a successful strategy for reducing HIV exposure among at-risk populations, including queer-identifying people, black and transgender women, and drug users. However, only a quarter of the 1.2 million people recommended for PrEP in Pennsylvania have a prescription. In Pennsylvania, only pharmacists in conjunction with a physician can provide PrEP, so allowing pharmacists to prescribe the drug alone would drastically increase access.
The results show that enabling pharmacists to provide PrEP alone would improve access in 27 of Pennsylvania’s 67 counties. Most pharmacies within a sub-30-minute drive are in Allegheny and Philadelphia counties. Drive times in more rural parts of the state remain over 30 minutes. For people in these counties, a lack of any pharmacy is a a key issue.
Topological Data Analysis (TDA) is a rising method that provides new topological and geometric tools that can detect non-linear features, such as loops, in multidimensional data. Our study aims to apply this novel method to find data patterns of COVID-19 spreads in selected thirteen representative countries on six continents of the world and compare results among them. Briefly, TDA methods are useful for determining “features” in point-clouds, including clusters and loops. Furthermore, quantifiable differences in features of the data sets of different countries can suggest differences in public health policy among those countries. Our results suggest TDA can be a useful initial data tool to search for anomalies, which can then lead to a more comprehensive analysis combined with other techniques. Using TDA, we were able to identify three major groups of countries based on their virus data patterns. Australia, India, South Korea, and Taiwan are very similar, while Great Britain, Peru, and France have very different patterns from those of other countries. Next, the death-to-case ratio and death per million among countries were investigated. We also examined in detail the public policy and other reasons behind the similarities and differences of the TDA results and suggested possible successful public policies at national levels for a future pandemic.
This study examines the mechanisms of spatial variation in intergenerational mobility (IM) and mental health in United States (US) counties. We explicitly emphasized the effects of four aspects of urban sprawl—density, mix of uses, centering, and accessibility, and natural environment and their interaction with socioeconomic factors. We found that while employment centering negatively affected IM, population centering enhanced IM. Typical livable city indicators of walkability, mixed-use development, and a jobs-housing balance improved IM. Urban sprawl variables also indirectly influenced IM through inequality, segregation, social capital, and unemployment. We also found that the Black population share had the largest indirect and total effects on IM. In terms of health outcomes, results show job sprawl, land mixed use, job mixed layout and jobs-housing balance mainly indicators of work-life balance and quality of life, can effectively reduce the risk of people being depressed. Greenspace can make people relaxed and absorb pollutants, thus can improve mental health, and this effect is more obvious in urban area. The increased concentrations of air pollutants, such as PM2.5, CO and O3, and more precipitation lead to more depression. This study has shown that enhancing IM requires more than reducing segregation and increasing density, and that effective treatment of mental health must incorporate built and natural environments.
In the past 5 years, Philadelphia has seen economic boom, COVID-19 and its concurrent economic bust, and the subsequent, if halting, recovery. Has the recovery been equitable? What economic sectors are still strong in this "new normal?" What issues in infrastructure building and transportation have been seen since the recovery began in 2021? And what does this mean for larger cities as they seek to allocate investment in infrastructure for the future?
The Geography Division of the Census Bureau has developed an automated change detection process using Artificial Intelligence and Machine Learning (AI/ML) to perform updates and maintenance to the Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System. Using Sentinel-2 satellite imagery and Google Earth Engine, data scientists can apply large-scale cloud compute with open-source python scripts to multiple vintages of moderate resolution imagery to identify areas of new construction. Once these areas are identified, staff use machine learning to perform object extraction to capture the building footprint for new structures. These building footprints will enhance the accuracy of incoming addresses data, as well the existing address locations, and will serve as a reference for all spatial updates in the MAF/TIGER System. In addition, the use of automated change detection methods and AI/ML creates operational efficiencies for geographers by focusing attention on areas in which change has occurred and updates are needed and new geospatial data may need to be acquired.
Geospatial data underpin all of the Census Bureau’s operations and analytical activities. The availability of new spatial and address source data has opened an opportunity for the U.S. Census
Bureau's Geography Division to apply new methods to update and maintain the Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System. National parcel files, automated change detection output, and building footprint data will be housed in the Geography Division's Intelligence Database (ID), which positions these new data sources alongside MAF/TIGER System data at the census block-level. This database provides a constantly maintained and updated repository of geospatial information at the census block-level, facilitating more effective assessment of change or stability as well as more effective decision-making in the management of geospatial information
The use of grid cells for data presentation and analysis has increased worldwide in recent years and offers several advantages over traditional small geographic units, including comparability, temporal stability, and uniformity. In this presentation, I discuss the Census Bureau Geography Division's Grids Project, which is focused on research and development leading to adoption of one or more grid systems for use in tabulating and presenting statistical data. The presentation will describe the advantages and known use cases for grids and the current state of the Census Grids Project. There will also be an opportunity for attendees to provide feedback regarding their own potential use cases for gridded data.
The Census Bureau’s Frames Program envisions enterprise-wide frames that are linkable in nature, agile in structure, accessible for production or research on a need-to-know basis and that adhere to best practices in terms of technology usage, data management, and methodology. The overarching goals of increasing utility and efficiency of data management for the variety of Census Bureau operations while minimizing burden on respondents drive this vision. The Geospatial Frame—the Master Address File/ Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System—forms the backbone of the enterprise-wide set of linked frames, with geography serving as the organizing principle underpinning all of the Census Bureau’s activities. In this presentation, I will discuss the goals of the Frames Program with a focus on how geospatial information linked to other foundational data can improve census and survey operations and data analysis as well as how use of information in the Business, Job, and Demographic Frames can enhance and augment data in the Geospatial Frame.
In this session, we will focus on best practices and innovation across Census and the data lifecycle. GIS can be used to improve accuracy and create efficiencies across the statistical business process. Modern Statistical organizations are now leveraging GIS for planning, data collection, operations management, analysis, visualization and dissemination. We will speak to Spatial Data infrastructures and Esri’s new SDMX integration as well as share examples from around the globe where GIS is making a difference for decision making at the local level.
“Equality” often means that each individual or group of people is given the same resources or opportunities. However, “equity” has emerged as something even more important because it recognizes that each person or group has different circumstances, requiring different amounts of resources and opportunities. In this session we will explore examples that highlight how GIS and spatial tools can be used to better understand issues of equity and burdens such as access to services, vehicle, issues of poverty and more.
Native Canadians are the fourth pan ethnic group (6.1%) in Canada. As a minority ethnic group, they exhibit unique population characteristics. Using the 2021Canadian Census Data, this paper explores the population characteristics of Native Canadians. Canadian Natives are broadly classified into three groups: Indians, Inuit, and Métis. Indians are believed to have entered North America through the Bering Sea about 10,000 to 30,000 years ago. Similarly, Inuit entered North America through the same land bridge with Asia that existed during the Pleistocene era. Over the years, the three groups had maintained different relationships with the federal government.
Apart from maintaining different relationships with the federal government, the three groups exhibit unique population characteristics. While the population of Métis increased at about 6.3% between 2016 and 2021, Inuit and Indians experienced an increase of about 8.3% and 9.7% respectively. The rate of increase was smaller for Registered or Treaty Indians (4.1%), compared to non-Registered or non-Treaty Indians (27.2%). Comparatively, the growth of the non-Native population was much lower (5.3%). Several factors including high fertility rates among Native Canadians, and a change in census definition of Aboriginal Canadians accounts for this phenomenon. Other population characteristics examined in this presentation include geographic distribution and use of Native languages. The analysis indicates that Ontario accounts for the largest concentration of Aboriginal Canadians. However, the largest provincial/territorial concentration of Aboriginal Canadians occurs in Nunavut (85.8%), Northwest Territories (49.6%) and Yukon (22.3%).
Every year, over a million Ohio drivers have their license suspended for reasons that have nothing to do with being a bad driver. Known as debt-related suspensions (DRS), they severely limit personal mobility, create a nearly inescapable cycle of debt, and are not spread evenly across communities. We address two fundamental research questions relating to DRS.
First, we analyze the demographic and economic characteristics of DRS-clustered communities. DRS are not spread evenly over the landscape, and so we begin by identifying areas of significant debt-related suspension concentration. Matching our DRS data to data from the American Community Survey, we then identify, compare and contrast the demographic and economic characteristics of these DRS clusters.
Second, we examine the social service needs of individuals in DRS clustered communities. The suspension of a driver’s license is likely one of many related challenges. To better understand their scale and scope, we analyze the nature and distribution of calls to the region’s social service hotline (2-1-1) across the previously identified DRS-clustered communities.
Simple and powerful location analytics to identify, test, and map the significance of geographical disparity in urban hazards is developed. Specifically, at a spatial granular unit, a minority’s relative proportion to its general proportion across a region is defined as location amplitude index (LAI). A significant LAI indicates abnormal aggregation of a minority at a location, which potentially experiences significant hazards. Comparing a minority’s LAI with the White’s LAI, we then develop another measurement of location amplitude disparity index (LADI). LADI hence is used to statistically test the significance of a minority’s disparity at a geographical granular unit. Using the 100-year floodplains in Birmingham, Alabama as the study areas, LAI and LADI identify and test geographical disparity of the Hispanic in the Valley Creek floodplain, insignificant (p > 0.5), and racial disparity of the African American is much significant with p values < 0.0001. This new location analytics of LAI and LADI fill the knowledge gap of spatial analysis of ethnic disparity in hazard study. LAI and LADI provide precise geographical and demographic measurements for equitable solutions to climate hazards, which often disproportionately influence underserved communities.
Research increasingly links the HOLC neighborhood rankings of the 1930s (a process colloquially known as redlining) with continued inequality and uneven patterns of disinvestment that negatively impact communities of color in many U.S. cities. Less research has examined how the HOLC neighborhood rankings might affect neighborhood level variations in sustainability across individual cities. This research seeks to address this deficiency by examining if there is a correlation between the HOLC’s neighborhood rankings for Pittsburgh neighborhoods and the distribution of variables that measure two of the three pillars of sustainability, environmental and social equity.
The research was conducted using ArcGIS Pro version 2.9.1 (2021). Data on tree equity scores, tree canopy and parks were used to measure environmental equity. Data on bike lanes were used to measure social equity. ArcGIS software was used to overlay this data on the HOLC rankings for Pittsburgh city neighborhoods, calculate spatial statistics, perform buffer analyses, and process raster layers.
The results of the analysis show that environmental and social equity are positively correlated with HOLC grade. However, the relationship is nuanced. Neighborhoods ranked as ‘best’ (A) and still desirable’ (B) had higher tree equity scores and more extensive tree canopy than neighborhoods ranked as declining (C) and hazardous (D). Concomitantly, this suggests that residents of neighborhoods ranked A and B enjoy lower levels of air pollution and improved mental health than residents of neighborhoods once ranked C or D. However, neighborhoods ranked declining (C) and hazardous (D) had more access to parks and bike lanes.
Planning requires the alignment of geographic data. GIS was a tool that should have helped in meeting this need, but that promise has not been met. The first Roundtable will look at the alignment problems which relate to the Red-Blue division in the US, essentially matters of scale.
The use of Social Index Matrixes to help predict market value of products such as green energy adoption and understanding the impact of regional adaptations of technology that may reduce the carbon footprint of the trucking industry are two examples of reserch areas where "unstructured data" holds the key to uncovering underlying driving forces that may lead to improvments in specific conditions. In the era of Big Data unstructured data is a large challenge for both industry and government. For industry it is a financial question of capturing market shares, reducing delays, or improving product use. It’s a problem that in many cases needs a spatial analysis and commonly requires cultural, social, and political perspectives and understandings. As AI promises answers to many questions, practical answers to be addressed from unstructured data require intellect from human geographers and other spatial scientists. This round table discussion invites industry, government and academia to explore this burgeoning area together where geographic practitioners can seek career directions and the academy can undertake research to address questions associated with unstructured data.
In recent years, innovations in GIS technology and an increase in accessibility of those technologies has led to greater intersectionality between geography and other fields in science and the humanities. In an age where STEM fields increasingly pull funding from humanities programs in universities around the country, staying on top of modern methods and practices is critical for the survival of these disciplines. By integrating education in GIS software and practices, history programs can increase their intersectionality with STEM disciplines and help to usher in a new age of digital history, driven by accessible data and wide-ranging public impact. By broadening its reach and making history more available to the public history can thrive in the fast-paced modern world and prove its worth to university administrations around the country. This starts with introducing digital history tools to undergraduate students, giving the historians of tomorrow the tools that they need to succeed and thrusting history, for the first time on a large scale, into the digital sphere.
This I start 1 of a 3-hour workshop (offered in three parts) will introduce attendees to several unusual and unique geocoded historical data resources on land snails held at the Carnegie Museum of Natural History and other museums across the United States. The workshop will be led by Tim Pearce (Assistant Curator of Mollusks at Carnegie Museum of Natural History), Susan Lucas (faculty member in the Urban Studies program) and Josh Cannon (Scholar-Mentor, Office of National Scholarships, David C. Fredrick Honors College, University of Pittsburgh).
Participants should have some GIS expertise. A basic knowledge of Excel will be helpful but is not required. Depending on their level of expertise and comfort, participants will work with either cleaned, ready to map or uncleaned/ uncorrected data. Participants should bring their own laptop computers.
Students experienced in GIS will be on hand to help participants.
In the first part of the workshop participants will learn basic land snail biology, discuss problems with the data including use of inconsistent terminology, inaccurate georeferencing and search effort.
This part 2 of a 3-hour workshop (will introduce attendees to several unusual and unique geocoded historical data resources on land snails held at the Carnegie Museum of Natural History and other museums across the United States. The workshop will be led by Tim Pearce (Assistant Curator of Mollusks at Carnegie Museum of Natural History), Susan Lucas (faculty member in the Urban Studies program) and Josh Cannon (Scholar-Mentor, Office of National Scholarships, David C. Fredrick Honors College, University of Pittsburgh).
Participants should have some GIS expertise. A basic knowledge of Excel will be helpful but is not required. Depending on their level of expertise and comfort, participants will work with either cleaned, ready to map or uncleaned/ uncorrected data. Participants should bring their own laptop computer. Students experienced in GIS will be on hand to help participants.
In the second part of the workshop, participants will have the opportunity to (1) produce maps showing the distributions of various land snail species, and (2) map temporal changes in various land snail species.
This 3-hour workshop will introduce attendees to several unusual and unique geocoded historical data resources on land snails held at the Carnegie Museum of Natural History and other museums across the United States. The workshop will be led by Tim Pearce (Assistant Curator of Mollusks at Carnegie Museum of Natural History), Susan Lucas (faculty member in the Urban Studies program) and Josh Cannon (Scholar-Mentor, Office of National Scholarships, David C. Fredrick Honors College, University of Pittsburgh).
Participants should have some GIS expertise. A basic knowledge of Excel will be helpful but is not required. Depending on their level of expertise and comfort, participants will work with either cleaned, ready to map or uncleaned/ uncorrected data. Participants should bring their own laptop computers. Students experienced in GIS will be on hand to help participants.
In the final part of the workshop, participants will be given the opportunity to examine how climate change and conservation of land snail species may impact their distribution.