Infrastructures constructed in Japan are estimated to age rapidly in the future. Hence, a method to efficiently inspect the infrastructures is needed. The purpose of this study is to verify that it is possible to detect the void near surface and flaking in the subway tunnel lining by the infrared thermography camera. At first, we acquire the data by infrared measurement system while moving. Next, we extract the void near surface and flaking by analyzing the infrared measurement. We have confirmed the efficacy of our proposed technique compared to conventional tapping sound investigation method. Furthermore, in the present study, we have been able to capture a very small temperature difference of even 0.05 degree centigrade.
Various measurement systems have been developed in order to solve the problem of superannuated infrastructures. Recently the utilization of 3D data became general technique that the measurement with the laser scanners (Terrestrial laser scanners and Mobile mapping systems) is one of the effective techniques. The advantage of 3D laser measurement is able to acquire the 3d data of spatial area and manage the data as surface. The combination of the laser scanning system and other techniques is expected to improve the data quality.
In recent years, many of the infrastructures that were made in the high-growth period are aging. At the same time, number of maintenance engineers for the infrastructures has been becoming insufficient. To solve these problems, we have developed a maintenance supporting system for road and structures. This system has the ability to utilize the point cloud measured by the MMS for such as creation of drawing for consultation, creation of CAD, FEM modelling, simulation of inspection work, and so on. This paper reports the state-of-the-art functions that have been developed for the system.
To control and preserve peat swamp forests, which have a significant impact on global warming, it is essential to effectively monitor forest degradation and recovery. This study examined a land cover classification method that considers not only the extent of vegetation but also the vegetation height and density by comparing airborne laser scanning data with data collected from field surveys. The laser scanning data that covered tropical peat swamp forests in Central Kalimantan Province, Indonesia, were obtained in 2007 and 2011. We also calculated the land cover changes from the difference between land cover ratios at the two different time periods after the land cover classification for the study area using the above-mentioned analysis method. Technically, it became clear that although the vegetation in the study area had been said to be degrading and decreasing due to agricultural land developments, it was actually recovering and increasing, judging from the amount of land cover changes during the four years. Thus, this analysis method is effective for clarifying detailed changes in vegetation height and density and further understanding the land cover changes in tropical rainforests, where vegetation grows faster than in cool-temperate and temperate zones.
We analyze and evaluate a correlation between fecal bacteria (Escherichia coli, fecal indicator bacteria and enterococci) and land use data for each month in the Oita River Basin. In these calculations, we consider the optimal range based on land use data from the observation points of the fecal bacteria. As a result of the analysis, we found that the correlation of agricultural land expect rice field is high in land use, and the correlations of the fecal bacteria are high in the case of using land use data from 400 to 500 m radius.
We propose a new classification feature for airborn laser scanner data by using bilateral minimum/maximum filters for classification. Through experiments which are classified airborn laser scanner data to building, ground, and tree, we verify the effectiveness of the proposed feature. Furthermore, we show that it can perform a highly accurate classification by combining the proposed feature and a conventional feature (Lodha et al., 2006). Finally we comment on the respects in which the proposed feature is improved and on future prospects.
We will propose a new method of water level measurement using river monitoring images taken by the closed circuit television (CCTV). Our method is featured by the definition of the water measure model, which in advance we have built from an image taken at the time of low water level. Generally the correlation between the observation images and the water measure model is enough strong. Therefor the implementation based on the method has provided robust measurement results through various observation conditions of light and water surface. Furthermore, since our method doesn't require high frame rate, the measurement can be stable by even use of night low rate video images.