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Alawadhi, A, Eliopoulos, C and Bezombes, F (2024) Temporal Monitoring of Simulated Burials in an Arid Environment Using RGB/Multispectral Sensor Unmanned Aerial Vehicles. Drones, 8 (9).
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Temporal Monitoring of Simulated Burials in an Arid Environment Using RGB Multispectral Sensor Unmanned Aerial Vehicles.pdf - Published Version Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
For the first time, RGB and multispectral sensors deployed on UAVs were used to facilitate grave detection in a desert location. The research sought to monitor surface anomalies caused by burials using manual and enhanced detection methods, which was possible up to 18 months. Near-IR (NIR) and Red-Edge bands were the most suitable for manual detection, with a 69% and 31% success rate, respectively. Meanwhile, the enhanced method results varied depending on the sensor. The standard Reed–Xiaoli Detector (RXD) algorithm and Uniform Target Detector (UTD) algorithm were the most suitable for RGB data, with 56% and 43% detection rates, respectively. For the multispectral data, the percentages varied between the algorithms with a hybrid of the RXD and UTD algorithms yielding a 56% detection rate, the UTD algorithm 31%, and the RXD algorithm 13%. Moreover, the research explored identifying grave mounds using the normalized digital surface model (nDSM) and evaluated using the normalized difference vegetation index (NDVI) in grave detection. nDSM successfully located grave mounds at heights as low as 1 cm. A noticeable difference in NDVI values was observed between the graves and their surroundings, regardless of the extreme weather conditions. The results support the potential of using RGB and multispectral sensors mounted on UAVs for detecting burial sites in an arid environment.
| Item Type: | Article |
|---|---|
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences G Geography. Anthropology. Recreation > GN Anthropology T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Biological & Environmental Sciences (from Sep 19) Engineering |
| Publisher: | MDPI |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 23 Sep 2024 10:07 |
| Last Modified: | 23 Sep 2024 10:15 |
| DOI or ID number: | 10.3390/drones8090444 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/24216 |
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