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Publication Date
2025
Document Type
Poster
Degree Type
Graduate
Department
Geography, Geology and the Environment
Mentor
Dr. Wondwosen Seyoum
Mentor Department
Geography, Geology and the Environment
Abstract
Soil moisture plays a crucial role in nutrient cycling, plant health, and water quality, particularly within saturated riparian buffers (SRBs). SRBs are vegetated zones designed to reduce nutrient runoff from agricultural fields, improving water quality. This study employs Unmanned Aerial Systems (UAS) and machine learning to generate high-resolution soil moisture maps within SRBs, aiming to better understand how soil moisture variability influences nutrient cycling processes and hydrological dynamics. Using the T-3 site in CentralIllinois as the study area, this research will analyze the spatial distribution of soil moisture and the factors contributing to its variability, including vegetation, topography, and weather conditions.
Traditional soil moisture monitoring methods, such as in-situ sensors and satellite imagery, face limitations in spatial resolution, coverage, and operational efficiency. To overcome these challenges, this study integrates UAS-mounted thermal and multispectral sensors to collect high-resolution imagery. These datasets will be processed through machine learning algorithms to produce accurate and reliable soil moisture estimates.
The key research objectives include mapping soil moisture variation at the T-3 site, identifying the primary drivers of this variability, and bridging the methodological gaps between traditional and modern monitoring approaches. The findings aim to optimize SRB management practices for improved nutrient retention and water quality outcomes while advancing the application of UAS-based remote sensing for environmental monitoring.
This study will test the following hypotheses:
- Soil moisture is expected to be highest in the early morning due to dew accumulation, resulting in a lower radiometric thermal signature compared to the afternoon when surface moisture decreases due to evaporation.
- A strong positive correlation is expected between vegetation indices (NDVI, EVI, red-edge band) and soil moisture, while an inverse relationship is anticipated between thermal imagery and soil moisture content, as drier soils exhibit higher surface temperatures.
Ultimately, this research seeks to answer the central question: What is the variation of soil moisture within the saturated buffer zone at the T-3 site, and what factors account for this variability? The outcomes will contribute to improved environmental monitoring techniques, enhance precision agriculture strategies, and inform land management policies for sustainable water quality improvement.
Recommended Citation
Timah, Jackline, "High-resolution mapping of soil moisture variation in a Saturated Riparian Buffer (SRB) using UAS thermal and Multispectral Imagery" (2025). University Research Symposium. 498.
https://ir.library.illinoisstate.edu/rsp_urs/498
