Nor Afiqah Adriana, Roslan (2022) Application Of Unmanned Aerial Vehicle (UAV) Photogrammetry Method For Rock Mass Rating Analysis Of A Rock Slope. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Bahan dan Sumber Mineral. (Submitted)
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Abstract
Rock mass characterization is the first step in defining rock mass quality and stability. There are many rock mass classification schemes which are frequently used for different purposes such as for estimation of strength and deformability of rock masses, stability of rock slopes and underground mining. Several techniques have been used in mapping the discontinuities of rock mass rating of a rock slope in this research such as manual mapping and UAV photogrammetry. The aim of this project is to study the geological properties of limestone rock, to analyse the rock mass properties of limestone rock using Rock Mass Rating (RMR) system and to compare the mapping method between the Unmanned Aerial Vehicle (UAV) and the conventional method. The software used in this project are Agisoft Metashape and Discontinuity Set Extractor (DSE). Next step is collection of data from case study area which then will proceed to the laboratory test such as point load test index. Based on the rock mass rating from manual mapping and point load strength index, this limestone is classified as “good rock”. From the mapping method between manual mapping and DSE analysis it shows that UAV mapping validated to manual mapping. However, the advantages using the UAV photogrammetry was able to obtain high precision of image of the discontinuity on slopes that are difficult to access on foot and managed to get more than four (4) joint sets which cannot obtain by manual mapping.
Item Type: | Monograph (Project Report) |
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Subjects: | T Technology T Technology > TN Mining Engineering. Metallurgy |
Divisions: | Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraan Bahan & Sumber Mineral (School of Material & Mineral Resource Engineering) > Monograph |
Depositing User: | Mr Engku Shahidil Engku Ab Rahman |
Date Deposited: | 15 Feb 2023 04:46 |
Last Modified: | 15 Feb 2023 04:46 |
URI: | http://eprints.usm.my/id/eprint/56964 |
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