Open AccessProposing a Method to Analyze Slope Displacement Using the Distance Image Data of Depth Camera
Author(s) -
Yasuhiro Onoue,
Tomohiro Ishizawa,
Toru Danjo,
Teruki Fukuzono
Publication year - 2021
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2021.p1086
Subject(s) - displacement (psychology) , typhoon , extensometer , geology , remote sensing , data set , computer science , set (abstract data type) , orientation (vector space) , process (computing) , artificial intelligence , computer vision , geodesy , mathematics , engineering , geometry , structural engineering , psychology , oceanography , psychotherapist , programming language , operating system
Sediment disasters have occurred with higher frequencies in recent years because of local heavy rains caused by line-shaped precipitation systems and torrential rains accompanying large typhoons. Since rescue operators are constantly under physical risk at disaster sites, there is a need for technologies to predict the occurrence of secondary disasters. The authors research the measurement of slope displacements by focusing on a depth camera that is readily deployable, can be easily set up, and enables monitoring of an extensive area but does not require expert knowledge to carry out measurements. In this process, we confirmed the difficulty of measuring slope changes preceding failure when the depth camera (DC) is set at a distance because of the large measurement errors caused by the limited depth resolution and poor measurement conditions under rainfall. In this study, we propose a new method for analyzing depth image data obtained by a depth camera and verify its validity for displacement measurements. After comparing the previous and proposed methods, we could confirm that the latter enables one to detect slope changes from minute deformations. When compared with the results of extensometers that directly measured the slope, we found that the results displayed similar tendencies of increase. Therefore, by measuring displacements preceding a slope failure using a depth camera and analyzing the depth image data acquired using the proposed method, we found that it is possible to detect minute changes that precede slope failures.