37-22 Using gprMax to Create Numerical Models of No Casket Burial Scenarios

Session: Geoscience Research Poster Showcase by 2YC and 4YCU Undergraduate Students

Poster Booth No.: 145

Presenting Author:

Alana Jornacion

Authors:

Jornacion, Alana Isidro¹, Schneider, Blair Benson², Alves Borges, Ayla³

(1) Allan Hancock College, Santa Maria, California, USA, (2) Kansas Geological Survey, University of Kansas, Lawrence, Kansas, USA, (3) University of Kansas, Lawrence, Kansas, ,

Abstract:

Human approach to death and subsequent burial is fundamental to who we are, shaping cultures over centuries of practice. That said, there is a large gap in the written documentation of certain burial regimens, including those in 19^th to early 20^th century America. During that time period, there were many cultural and technological shifts occurring, which changed how certain burials were performed. Many different groups of people were passing through Kansas during this time period, leading Kansas to reflect those differing burial practices. A significant portion of burials from this time period are located in potter’s fields, which were areas that were often used to bury unidentified, unclaimed, or destitute individuals. 

 

Due to the ethics around modern day burial preservation, excavation has heavy restrictions in place. Instead, a noninvasive way to learn more about these sites is to use ground penetrating radar (GPR). GPR transmits electromagnetic waves through the subsurface and these waves return reflections when they encounter different materials.

 

Despite its promise, GPR data is often difficult to interpret due to the noise produced by other (non-burial) naturally occurring objects in the subsurface. There is little research done on how the size of the human (adult, child, or infant sized) and the stage of bone deterioration affects GPR detection of burials. For this research, we used gprMax, a Python software, to simulate different burial conditions in GPR data. In gprMax, several variables can be tested and controlled, including burial depth, body size, stage of bone deterioration, GPR antenna frequency used, and soil type. The results of the models are then comparatively analyzed to actual GPR data from the Alma City Cemetery in Alma, Kansas. The goal of this analysis is to improve data interpretation and allow for more comprehensive trend categorization. Future research can include more complex modeling scenarios to help further improve GPR burial interpretation.

 

This work was conducted as part of the Geo-Launchpad internship program, supported by the NSF NGF operated by EarthScope Consortium.

 

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

doi: 10.1130/abs/2025AM-21664

© Copyright 2025 The Geological Society of America (GSA), all rights reserved.