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University of Nebraska-Lincoln Libraries GIS Day 2023: Mini-conference

Join us on November 13, from 1:15-4:30 p.m. in Love Library South, Room 221 (Peterson) to enter the fascinating world of Geographic Information Systems (GIS). Whether you're a GIS enthusiast or just curious to learn more, join us for informative talks by GIS experts and graduate students, and networking opportunities. A tour of the Archives & Special Collections will be offered. Free, open to the public and refreshments included.

The presentation topics cover a wide range of fields related to Geographic Information Systems (GIS) and remote sensing, including ecological studies, desertification assessment, career opportunities in GIS, spatial analysis applications, scale relevance in reflectance studies, geospatial approaches for addressing historical remains, disease risk estimation, urban and population studies, and agricultural applications for nitrogen management and sustainability.

Sponsors: University Libraries, the School of Natural Resources, and the School of Global Integrative Studies. 

Event Photos: 






Photos were taken by Erin Colonna and Wenjie Wang


GIS day event on Nov. 13th (1:00pm-4:30pm)

Join Us Anytime – No RSVP Needed!

1:00pm-1:15pm    Reception

      With tables for flyers, light snack


      Presentation by Casey DunnGossin (State of Nebraska GIS Coordinator)


      Mini-conference Session 1 

3pm–3:30 pm activities:

      Archives and Special Collections Tour by Traci Robinson

      Refreshment of snacks and drinks


      Mini-conference Session 2

Mini-conference Presentation Schedule:

Utilization of GIS in tracking disinterment and movement of unknown US WWII War dead: Foundations for a geospatial approach to addressing commingled remains (by Ella Axelrod, SGIS; 1:30 – 1:45 pm)

In the aftermath of World War II, the US was faced with the monumental task of finding and identifying over 405,000 service members who did not survive the conflict. Of these 405,000, 81,000 remain missing and 2,498 remain unidentified in cemeteries across Europe alone. Often, these individuals were interred and disinterred multiple times. Each instance of disinterment and movement is an opportunity for commingling to occur. DNA testing is an oft relied upon method for distinguishing between individuals in these cases but can be time consuming and expensive. Further, when tests are conducted and results do not indicate a match with a suspected individual, this can compound the difficulty in establishing the unknown individual's identity. This project aims to establish a foundation for a spatially oriented approach to addressing commingling in these cases and aid in creating a "shortlist" of suspected individuals that may be a positive matcoli-p0[[h. Through the creation of a geospatial tracking system, each unknown individual's path is traced in relation to known locations of origin and interment and can be analyzed in tandem with all unknown individuals that they have crossed paths.

Relevance of scale in grassland reflectance (by Catherine Chan, SNR; 1:45– 2:00 pm)

The use and fusion of remote sensing information are heavily dependent on scale. This can entail aspects of space and time for one dataset, but also the integration of multiple datasets of varying scales or resolutions. Selecting appropriate resolutions is critical in making accurate interpretations and assessments. I will present and provide a demonstration of the different types of scales mainly related to spectral reflectance data, LiDAR-derived digital elevations models, and ground measurements, within a grassland landscape and how they can impact results.

Bivariant mapping Omaha’s population and clothing store shifts, 1945-2020 (by Heather Bloom, SGIS; 2:00 – 2:15 pm)

After World War II, the central downtown shopping district relocated to the suburbs as the shopping mall. Showing this change in land use is best illustrated by communicating multiple types of change, or bivariant mapping.  Bivariant mapping presents two or more variables on one map by combining two or more contrasting sets of symbols or colors.  Using bivariant mapping to show shifts in clothing stores is advantageous to visually link the movement of population as suburbanization increased.  This presentation will discuss map choices made when combining multiple data sets, from sources such as U.S. Census Bureau, Douglas County-City of Omaha GIS, and Omaha City Directories.

Assessing the use of vegetation index as a tool for nitrogen management in soybean (by Luzviminda Sazon, Agronomy and Horticulture; 2:15 – 2:30 pm)

Nitrogen limits production in high-yielding soybean fields, and this limitation varies across these fields.  However, there is no tool to predict nitrogen-limited fields. We took multispectral images around flowering in high-yielding soybean fields and preliminary results showed the potential use of the vegetation index as a tool to fine-tune the nitrogen management decision tool for soybeans.

The potential use of GIS and remote sensing in supporting sustainable oil palm plantation (by Rana Farrasati, Agronomy and Horticulture; 2:30 – 2:45 pm)

Discover the untapped potential of GIS in revolutionizing sustainable oil palm plantations. In this presentation, we will delve into the powerful combination of GIS technology, drone surveillance, and satellite imagery, which promises to enhance field condition monitoring, pest and disease detection, and decision-making processes, all geared towards promoting sustainability in the oil palm industry.

Crops to Urban Health:  Insights into the wide applications of spatial analysis within different sectors through the development of algorithms (by Noah Berkowitz, SNR; 2:45 – 3:00 pm)

The boundless utility of spatial analysis is underscored by its application across diverse sectors. Often, similar analysis occurs across different sectors. This presentation will discuss my experience from working in Health departments to working in agronomy departments, building algorithms that apply similar spatial analysis to understand geographic questions. These algorithms integrate domain-specific knowledge as a lever to enhance algorithmic accuracy and fuel subsequent research endeavors. Through a reflective discourse, this presentation aims to explain the transformative potential of spatial analysis and foster a cross-disciplinary dialogue on optimizing algorithmic / domain-driven approaches to address sector-specific geographic challenges.

*****Archives and Special Collections Tour (by Traci Robinson; 3:00 - 3:30 pm) ****

Estimating disease risk by integrating animal movement into mathematical models (by Alexis Beagle, Biological Sciences; 3:30 – 3:45 pm)

The goal of this work is to understand how supplemental feeding of elk alters animal movement and subsequent disease risk on the National Elk Refuge (NER) in Jackson, Wyoming. I used elk GPS data and a modelling framework called MoveSTIR (movement driven spatiotemporal infection risk) to create disease risk maps for years when managers fed and did not feed. I also compared the maps created from this framework with a more commonly used method of estimating spatial risk, kernel density estimates, to understand when one method may be more beneficial depending on disease and weather conditions.

Hyperspectral mapping of the effects of invasive eastern red cedar along the Niobrara River in Nebraska (by Lillie Hoffart; Biological Sciences; 3:45 – 4:00 pm)

Globally, woody encroachment — the expansion of native and non-native woody species — is increasingly threatening grasslands, forests, and other ecosystems, and eastern redcedar (Juniperus virginiana) (ERC) has been encroaching into the Great Plains over the last several decades. The goal of this project is to assess how ERC is affecting diversity in forested ecosystems but to do so requires information on ERC encroachment at fine scales and large spatial extents. Using high resolution hyperspectral remote sensing imagery of the Niobrara River Valley combined with ground truthing data from a forest inventory plot, we trained a support vector machine to identify ERC tree crowns. Applying this machine learning model, we mapped ERC over approximately 12 km2 of the Niobrara River Valley at 1m2 spatial resolution. This ERC map will be the basis for future analyses of spectral diversity across levels of ERC encroachment as a part of an integrated assessment of ERC impact on forests.

Desertification assessment using remote sensing & GIS in Al-Butana Area, Sudan 2000 – 2023 (by Suhib Hamid, BSE; 4:00 – 4:15 pm)

This project aims to assess these causes, and consequences of desertification during the last twenty years, to determine the land cover classes and sand changes during these years, to assess the extent and percentage of areas that affected by sand, and to explore the application of remote sensing and GIS technology for monitoring this phenomenon.

Career opportunities in GIS (by Shetu Akter, SNR 4:15 – 4:30 pm)

I will discuss job outlook, required skills and qualifications, types of GIS career and growth opportunities.

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