Comparative analysis and visualization of soil profiles at the meter spatial scale utilizing novel matrix and volume rendering techniques

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dc.creatorGonzalez, Jake (TTU)
dc.creatorSiebecker, Matthew (TTU)
dc.creatorPham, Vung
dc.creatorJordan, Cynthia (TTU)
dc.creatorWeindorf, David C. (TTU)
dc.creatorDang, Tommy (TTU)
dc.date.accessioned2024-01-19T20:03:59Z
dc.date.available2024-01-19T20:03:59Z
dc.date.issued2023
dc.descriptionFile under embargo until 08 November 2025. © 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstractThis research introduces a soil characterization technique involving four data visualization tools to help researchers and stakeholders interpret high dimensional soil data at the field scale. This technique involves visualizing a reduced dimensionality representation of elemental concentration and color data gathered via portable X-ray fluorescence (pXRF) spectrometer and NixPro color proximal sensors, respectively. Soil cores were collected from sites located in Lubbock and Lamb Counties, West Texas, USA. Thirteen core samples were collected from these sites in a star pattern with readings from proximal sensors at depths ranging between 0 and 100 cm at 10 cm intervals. The dimensionality reduction techniques utilize four visualization tools to represent soil composition data through multiple user-adjustable variables (i.e., mg kg−1 elemental concentrations and soil profiles), offering more insight and control compared to a single-variable approach. Through these tools and techniques, qualitative and quantitative conclusions regarding soil characteristics (e.g., elemental concentration variation, delineation of soil horizons, changes in soil color) can be formulated from the data and used in various applications. Areas where these novel software tools can be utilized potentially include rapid contaminant mapping in soils, characterization of diagnostic soil horizons (e.g., calcic, spodic, gypsic, etc.), micronutrient distribution at a field scale for precision agricultural purposes, and pedometrics.
dc.identifier.citationGonzalez, J., Siebecker, M. G., Pham, V., Jordan, C., Weindorf, D. C., & Dang, T. (2023). Comparative analysis and visualization of soil profiles at the meter spatial scale utilizing novel matrix and volume rendering techniques. Computers and Electronics in Agriculture, 215, 108377. https://doi.org/10.1016/j.compag.2023.108377
dc.identifier.urihttps://doi.org/10.1016/j.compag.2023.108377
dc.identifier.urihttps://hdl.handle.net/2346/97506
dc.language.isoen_US
dc.subjectElemental Concentration Data
dc.subjectData Visualization and Analytics
dc.subjectPortable X-Ray Fluorescence
dc.subjectNixPro Proximal Sensor
dc.subjectAlpha-Shape Scatter-Plot Matrix
dc.subjectDimensionality Reduction
dc.titleComparative analysis and visualization of soil profiles at the meter spatial scale utilizing novel matrix and volume rendering techniques
dc.typeArticle

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