Novel soil core visualization of diagnostic pedogenic features
| dc.contributor.committeeChair | Siebecker, Matthew G. | |
| dc.contributor.committeeMember | Weindorf, David C. | |
| dc.contributor.committeeMember | Deb, Sanjit | |
| dc.contributor.committeeMember | Dang, Tommy | |
| dc.creator | Jordan, Cynthia Marie | |
| dc.date.accessioned | 2022-08-25T20:11:28Z | |
| dc.date.available | 2022-08-25T20:11:28Z | |
| dc.date.created | 2022-08 | |
| dc.date.issued | 2022-08 | |
| dc.date.submitted | August 2022 | |
| dc.date.updated | 2022-08-25T20:11:29Z | |
| dc.description.abstract | Soil resources are critical for food production for a rapidly increasing population. Soils are traditionally mapped using a combination of field surveys and laboratory testing. However, while data obtained from traditional laboratory experiments are of great importance for land management, it requires time-consuming, costly techniques and can generate hazardous waste. Therefore, newer approaches are needed to increase data processing speed without sacrificing data quality. The use of proximal sensors offers such an approach. In this study, 39 soil cores were taken from southern Lamb County, TX, and northern Lubbock County, TX, for analysis via proximal sensors, and data were combined into a 3D Soil Visualization Tool (SVT). Three sampling locations of different spatial resolutions (100 and 200 m between each core) were utilized. Each collected soil core was sectioned into ten-centimeter segments (e.g., 0-10 cm, 10-20 cm, and so on) to a depth of one meter. Data from portable X-ray fluorescence (PXRF) spectrometry, were imported and interpolated into a three-dimensional model for visualization of elemental distributions throughout each sampling site. The interactive models allow for the visualization of soil properties such as elemental concentrations with depth. The data from traditional laboratory analyses (e.g., pH, electrical conductivity, and loss on ignition) were analyzed and plotted to show correlation via two-dimensional plot. The three-dimensional Soil Visualization Tool was utilized to confirm and capture the extent of spatial heterogeneity among chemical parameters which was not possible with two-dimensional correlation plots alone. This novel three-dimensional approach to viewing elemental distribution within the soil profiles provides for a large-scale interpretation of pedogenic processes. Visualization tools using proximal sensors allow for rapid and accurate soil data collection with reduced need for laboratory analysis. In addition to research endeavors and managing terrestrial lands, the three-dimensional soil core model can also be applied to extraterrestrial soils. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/2346/90029 | |
| dc.language.iso | eng | |
| dc.rights.availability | Access is not restricted. | |
| dc.subject | Soil science | |
| dc.subject | Proximal sensors | |
| dc.subject | PXRF | |
| dc.subject | Soil visualization | |
| dc.title | Novel soil core visualization of diagnostic pedogenic features | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Plant and Soil Science | |
| thesis.degree.discipline | Plant and Soil Science | |
| thesis.degree.grantor | Texas Tech University | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science |