Abstract
The objective of this research was to assess plant-soil relationships and evaluate the use of multispectral drone imagery in predicting revegetation potential and soil properties at mine-land waste rock dumps. Field sampling of soils and vegetation was conducted, followed by Bayesian statistical significance tests and linear discriminant analysis (LDA) to determine key soil variables influencing plant communities. Results indicated that pH and electrical conductivity (ECe) were significant factors in the LDA and identified several plant communities that were associated with similar soil types. In parallel, regression analyses were employed to correlate multispectral drone imagery with soil characteristics and plant cover. While multispectral imagery effectively predicted certain soil properties, it was less successful in forecasting revegetation potential (measured by remotely sensed percent plant cover). These findings highlight the potential and limitations of using multispectral drone imagery for predicting and mapping soil properties at waste rock dumps and selecting the most suitable species to plant as a method of precision reclamation.
Degree
MS
College and Department
Life Sciences; Plant and Wildlife Sciences
Rights
https://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Moon, Haley, "Precision Reclamation for Improving Mine-Land Reclamation Using Plant-Soil Chemical Analysis and Geospatial Technology" (2024). Theses and Dissertations. 10673.
https://scholarsarchive.byu.edu/etd/10673
Date Submitted
2024-12-10
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd13510
Keywords
plant-soil relationships, multispectral drone imagery, revegetation potential, soil properties, waste rock dumps, Bayesian statistical significance tests, linear discriminant analysis, regression analysis, remote sensing
Language
english
