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Analisis Deformasi Jembatan Akibat Banjir Bandang Berbasis Fotogrametri Jarak Dekat
Author(s) -
Larasaty Ayu Parsamardhani,
Martinus Edwin Tjahjadi,
Fransisca Dwi Agustina
Publication year - 2022
Publication title -
jambura geoscience review
Language(s) - English
Resource type - Journals
eISSN - 2656-0380
pISSN - 2623-0682
DOI - 10.34312/jgeosrev.v4i1.12013
Subject(s) - deformation monitoring , deformation (meteorology) , bridge (graph theory) , computer science , structural engineering , remote sensing , physics , geography , engineering , meteorology , medicine
Monitoring the deformation of objects in the natural disaster area is one of the anticipative steps to reduce losses. In this case, this is an attempt to implement mitigation for the safety and viability of the community. Until this time, many constraint factors in the process of obtaining information regarding the strength of the structure and the changes of shape and dimension (per time unit) of the objects, one of which is the high operational cost and the duration of data processing while using a conventional measuring instrument. Through this article, a fast, cheap, easy, and accurate alternative method to detect deformation of the bridge material structure due to flash flood is only by using a Digital Single Lens Reflex (DSLR) camera. The bridge’s structures were photographed and processed with proprietary software to obtain the retro-reflective coordinate of the target that has been evenly attached to the bridge surface as a reference point. From a series of periodic photoshoots conducted from July 2020 to July 2021, deformation of the bridge structure was successfully detected with a magnitude between 0.026 mm – 5.867 mm with a measurement accuracy level was 0.081 mm. With this measurement accuracy level, this system is able to detect the deformation of structures smaller than 0.1 mm, and even invisible deformation can still be detected. This article will explain the technique and methodology of deformation measurement quickly and accurately only with a DSLR camera.

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