A Literature Review on the Development of Remote Sensing in Damage Detection of Civil Structures
Khaled Ghaedi
Department of Civil Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia and Center of Research and Development, PASOFAL Engineering, 52200, Kuala Lumpur, Malaysia.
Meisam Gordan *
Department of Civil Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia and Center of Research and Development, PASOFAL Engineering, 52200, Kuala Lumpur, Malaysia.
Zubaidah Ismail
Department of Civil Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia.
Huzaifa Hashim
Department of Civil Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia.
Marieh Talebkhah
Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Seri Kembangan, Selangor, Malaysia.
*Author to whom correspondence should be addressed.
Abstract
Remote sensing technologies have a direct impact on gaining structural damage information due to their powerful flexibilities, such as wide field of view, non-contact, low cost, and fast response capacities. It is because remote sensing is often applied to monitor near-real-time damage for large-scale events. Therefore, diverse types of remote sensing data became available and various methods have been designed and reported for structural damage assessment. In this line, a number of remote sensing procedures have been proposed to develop an extensive range of temporal, spectral, and spatial parameters. In this study, a comparative review is conducted in order to present the applied remote sensing-based damage detection approaches in buildings and bridges. It should be noted that the survey is supported by an extensive list for up-to-date references. Based on this review, it can be concluded that remote sensing has widely attracted attentions in different structural engineering fields due to its ability in providing fast response in terms of continuous monitoring for large areas after a natural hazard.
Keywords: Remote sensing, structural health monitoring, damage detection, Internet of Things