On April 14, 2016, an earthquake of magnitude 6.5 occurred in the Kumamoto region, and two days later, on April 16, a larger earthquake (M7.3) occurred in the area. Surface faulting appeared intermittently from Aso city to Mifune town after the earthquake. It is important for understanding the mechanism and disaster prevention measures to grasp the deformation of surface faulting and their surroundings. This paper carries out comparison and difference of landforms using aeronautical laser data measured before and after the earthquake of April 16, and examines detailed deformation near the fault.
After the main shock of 2016 Kumamoto Earthquake (Mj7.3), coseismic wide-area crustal deformation was observed around Aso region in Kumamoto Prefecture, Japan. In this study, multi-temporal LiDAR DEMs and Digital Geomorphic Image Matching method was applied to measure ground displacements of 1m scale in wide-area.
As a result, seismic wide-area crustal deformation around caldera and displacements along a lot of surface ruptures of the earthquake faults were observed. Additionally, large lateral slides of the area of 1-2km diameter were observed in the flat caldera floor filled with unconsolidated sediment. Amount of displacements of these area were 1-4m.
After the main shock of 2018 Hokkaido Eastern Iburi Earthquake (Mj6.7), coseismic ground displacement or deformation was observed around eastern region of Sapporo City in Hokkaido, Japan. In this study, multi-temporal LiDAR DEMs and Digital Geomorphic Image Matching method was applied to measure ground displacements of meter-scale. As a result, local ground displacements and subsidence by lateral flow of valley fill embankment were observed in the developed residential land. These results were consistent with the results estimated by analysis of SAR Images.
The 2018 Hokkaido Eastern Iburi Earthquake brought about great numbers of landslides in the broad area of the eastern Iburi region, Hokkaido, especially Atsuma town. As emergency disaster response to the earthquake, PASCO Corporation carried out 1) taking oblique aerial photographs, 2) automatic extraction of landslides using optical satellite imagery (SPOT6), 3) detection of surface deformation with DInSAR analysis and 4) field surveys based on DInSAR analysis. This paper introduces the analysis of extraction utilizing optical satellite images with deep learning, which has been actively studied in recent years.
With the increase in natural disasters in Japan, the large amount of driftwood has a severe impact on the marine industry and environment. The Asia Air Survey Co., Ltd. conducts the aerial survey immediately after a disaster occurs and provides open data images of the damaged sites on the website. In this survey, the “driftwood map" was made to assess the distribution and quantity of driftwood, using the oblique photography from 2020 Kyusyu flooding.
For road mapping, it is important to add labels to point clouds captured by the Mobile Mapping System (MMS). Some automatic labeling methods have been proposed so far. However, in our experiment, conventional labeling methods were not sufficiently accurate for actual point clouds measured in Japan. In this paper, we propose a high-performance classification method that combines the multi-scale features of point clouds, the MMS specific features and the features obtained from point clouds mapped on the 2D image. The accuracy of the proposed method was evaluated using actual MMS data, and it was confirmed that the proposed method could achieve high recognition rate generalization performance. Our method can improve the accuracy of automatic labeling of point clouds, and is expected to improve the efficiency of map maintenance, which is a social infrastructure.
Estimating damage to forests by strong winds is presented. In this study, a method to detect disaster-stricken forests by using the normalized difference vegetation index (NDVI) ratio before and after a disaster was developed. Chiba prefecture was selected as the test area. Many trees in Chiba prefecture were fallen due to strong winds of the Typhoon 15 (T1915) in 2019. One Sentinel-2 MSI dataset before T1915 and three after it were used for detecting wind fallen trees (WFTs). NDVI ratios in pure pixels of WFTs (WFT100%) were examined. NDVI ratios in pure pixels of no WFT (WFT0%) were also examined. Three linear interpolation expressions between WFT100% and WFT0% for MSI dataset after T1915 were developed to estimate the area ratio of WFTs in each mixel. 78% of WFTs detected by visible interpretation of aerial photographs were located in pixels with the area ratio of WFTs greater than 0%. In contrast, 93.4% of pixels with the area ratio of WFTs greater than 0% actually included WFTs. This method is useful to estimate the distribution of WFTs in the wide area.
Various kinds of cameras such as 360°camera, action cameras, smartphones, and drive recorders have been utilizing as an on-board cameras for the construction of the Intelligent Transport Systems. However, there are still problems with efficient imaging using on-board cameras. These problems are the influence of sunshine, and shadow or occlusion by the person or cars. On the other hand, the high sensitive functions of consumer grade digital cameras are amazingly increasing, and high sensitive imaging such as ISO409600 was achieved.
In these circumstances, high sensitivity consumer grade digital cameras are enormously expected in imaging at night for solving the above problems, performance evaluations of high sensitivity consumer grade digital cameras are investigated in this paper.