Integration of satellite remote sensing and electrical resisitivity techniques for the detection of coastal erosion | |
| Author | Vithoune Phonekeo |
| Call Number | AIT Thesis no.GE-24-05 |
| Subject(s) | Coast changes--Remote sensing Erosion--Remote sensing Electrical engineering |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Geotechnical and Earth Resources Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | This research introduces an innovative methodology for detecting coastal erosion by employing Electrical Resistivity (ER) measurements to determine shoreline positions, subsequently comparing these findings with traditional Sea Masking techniques. Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to extract shoreline contours, thereby converting electrical resistivity data into shoreline boundaries. These ER-derived shorelines were then compared with visually interpreted Sea Masking shoreline delineations. The root means square error (RMSE) values ranged from 1.97 to 12.79 meters. The results suggest that ER-based shoreline delineation constitutes an effective approach for coastal monitoring.Following shoreline confirmation, rates of shoreline change over several years were assessed using ER-derived shorelines to evaluate coast evolution over time. Subsidence resistivity data was employed to gauge the susceptibility of the coast to erosion. Electrical Resistivity Imaging (ERI) and Vertical Electrical Sounding (VES) techniques facilitated the identification of subsurface materials and the measurement of resistivity. The ERI inversion delineated two principal geological units: the highly conductive Old Mangrove Clay Layer and the resistive Sand Layer. The Sand Layer was deemed highly erodible, whereas the Old Mangrove Clay Layer was considered to have low to moderate erodibility, according to Karim and Tucker Kulesza (2018)’s erodibility threshold. These categories of erodibility closely aligned with observed shoreline changes. Between 2021 and 2025, the southern coast exhibited the highest rate of 26.26 meters per year, where sediments of very high erodibility predominate. Overall, ER-based shoreline data effectively characterizes shoreline variability and subsurface erosion potential, thereby providing a robust foundation for coastal erosion monitoring and strategic management. |
| Year | 2025 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Geotechnical and Earth Resources Engineering (GTE)/Former name = Geotechnical Engineering (GE) |
| Chairperson(s) | Avirut Puttiwongrak; |
| Examination Committee(s) | Chao, Kuo Chieh;Virdis, Salvatore G.P.;Natthachet Tangdamrongsub; |
| Scholarship Donor(s) | AIT Scholarship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2025 |