Keywords: Tile drainage mapping, Proximal sensing, Remote sensing, Ground penetrating radar, Electromagnetic induction, Thermal and multispectral imaging
Accurate mapping of subsurface tile drainage systems is essential for understanding water and nutrient transport in agricultural landscapes. However, the exact locations of drainage pipes are often poorly documented. This project will investigate how different proximal and remote sensing techniques can be used to detect and map tile drains efficiently under real field conditions. Using insights from an existing research project, the student can work with different aspects in relation to high‑resolution UAV imagery (VIS, multispectral, and thermal), ground‑based geophysical measurements (e.g., GPR, EMI), and image analysis workflows to evaluate the detectability of drainage patterns across varying soil types, moisture levels, and crop conditions. The project may include field data collection, data preprocessing, and the testing of conventional and advanced image-processing methods, with the option to explore machine learning approaches for automatic detection of drain lines. The content will depend on the extent of the project.
Is field work part of the topic? Yes
Is lab work part of the topic? No
Is coding part of the thesis topic? Yes
Any time
AU Viborg
30 ECTS (IMSOGLO and Agrobiology): Theoretical thesis based on literature studies and/or analysis of issued and edited data sets.
45 ECTS (Agrobiology): Experimental theses in which the student is responsible for collection and analysis of his/her own original data
60 ECTS (Agrobiology): Experimental theses in which the student is responsible for planning, trial design and collection and analysis of his/her own original data
Allred, B.J., Martinez, L., Fessehazion, M.K., Rouse, G., Williamson, T.N., Wishart, D., Koganti, T., Freeland, R., Eash, N., Batschelet, A., 2020. Overall results and key findings on the use of UAV visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes. Agr Water Manage 232, 106036. https://doi.org/10.1016/j.agwat.2020.106036.
Koganti, T., Van De Vijver, E., Allred, B.J., Greve, M.H., Ringgaard, J., Iversen, B.V., 2020. Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument†. Sensors 20(14), 28. https://doi.org/10.3390/s20143922.
