Validation of High-resolution and Simple River Monitoring Technique using UAV-SFM Method
I GD Yudha Partama1, I Ketut Sumantra2, AAG Sutrisna WP3, Agus Sukma Yogiswara4
1I GD Yudha Partama*, Postgraduate Program of Regional Development Planning and Environmental Management, Mahasaraswati University, Denpasar, Indonesia.
2I Ketut Sumantra, Postgraduate Program of Regional Development Planning and Environmental Management, Mahasaraswati University, Denpasar, Indonesia.
3AAG Sutrisna WP, Department of Environmental Engineering, Mahasaraswati University, Denpasar, Indonesia.
4Agus Sukma Yogiswara, National Land Agency of Indonesia, Indonesia.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 5409-5413 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6926018520/2020©BEIESP | DOI: 10.35940/ijrte.E6926.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study tested the accuracy and precision of the UAV-SfM method, an automated photogrammetry technique called SfM (Structure from Motion) using multiple pictures taken by UAV (Unmanned Aerial Vehicle), in a section of Saba river, Yamaguchi, Japan. The method was applied in the submerged area as well as in the exposed area, taking into account the refraction at the water surface, for the first time in domestic rivers. When the resultant DEM (Digital Elevation Model) is considered as the map of riverbed elevation, the RMS (Root Mean Square) error and R2 (coefficient of determination) of UAV-SfM were 0.165 m and 0.93, respectively. In pixels with thick algae cover, large apparent overestimations reaching 0.351 m at maximum were observed because UAV-SfM actually measures the algae surface elevation, not the riverbed elevation. Error analyses also showed that the refraction correction method adopted in this study is working well in spite of its simplicity.
Keywords: Underwater photogrammetry, fluvial topography, Digital Surface Model, drone.
Scope of the Article: Digital Surface Model