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Open Access Knowledge and Scholarship

Date of Award

5-2025

Culminating Project Type

Thesis

Styleguide

apa

Degree Name

Geography - Geographic Information Science: M.S.

Department

Geography and Planning

College

School of Public Affairs

First Advisor

Jeffrey Torguson

Second Advisor

Mikhail Blinnikov

Third Advisor

Jalal Khalil

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

GIS, Spatial Interpolation, Aeromagnetic

Abstract

The number of spatial interpolation methods that have been applied to the extremely spatially anisotropic data capture that regularly occurs with aerial geophysical measurement surveys. The data capture methodology of the United States Department of Energy’s National Uranium Resources Evaluation (NURE) Aeromagnetic Survey consisted of near parallel flightlines spaced at three-mile intervals flown by helicopter with attached magnetometers taking measurements every second. Unfortunately, the applicability of many spatial interpolation methods is limited to rigid grids that can often be generalized to accommodate randomly distributed measurements, while uncommon or even rare generalization or even novel methods have continued to be developed for extremely spatially anisotropic data interpolation. Additionally, with the capability of machine learning algorithms to be trained to situation specific needs many new spatial interpolation methods relying on machine learning have been emerging in recent years. The machine learning technique Random Forest (RF) has been applied to spatial interpolation using various techniques implemented to prevent the occurrence of Zonal Artifacts, which are bounded zones of isolated prediction distributions, with boundaries arising from decision tree nodes utilizing the spatial coordinate data in splitting the node. This study set of to evaluate the baseline capabilities of seven spatial interpolation methods when applied to aeromagnetic flightline measurements while at the same time investigating the some of the characteristics of Zonal Artifacts when applied in this situation. When it comes to quick implementation particularly in situation where limited expertise is a concern the long-established Thin Plate Splines (TPS) can be expected to perform with up to moderate accuracy requiring little to no parameter tuning to achieve preliminary results. The other interpolation methods explored show some promising capabilities where expertise in the study area, parameter tuning, data collection procedures, etc. can be utilized to enhance the accuracy. In the evaluation of RF Zonal Artifacts, the position of zone boundaries were regularly situated along flightlines with the alignment accentuated in the local RF variation Geographical Random Forests (GRF) which permits the boundaries to follow perturbations in the flightline. The alignment of Zonal Artifact boundaries was also shown be associated with Easting, Northing, and Elevation spatial coordinates.

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