Abstract
Abstract. A large-scale disaster has occurred due to the earthquake. In particular, 20% of the world's earthquakes with a magnitude of 6 or more occur near Japan. Damage analysis of buildings by image analysis have been effectively carried out using optical high-resolution satellite images and aerial photograph with spatial resolution of about 2 m or less. In this study, the damaged buildings caused by large-scale and continuous earthquakes in Kumamoto, Japan that occurred in April 2016 was selected as a typical example of damaged buildings. For these earthquake event, the applicability of damage distribution of buildings and recovery/restoration status by texture analysis was examined. The applicability of the representative in the dissimilarity texture analysis methods Gray- Level Co-occurrence Matrix (GLCM) method by image interpretation in the case of a large number of collapsed and wrecked buildings in a wide area was assessed. These results suggest that dissimilarity was applicable to the extraction of damaged and removed buildings in the event of such an earthquake. In addition, the analysis results were appropriately evaluated by comparing the field survey results with the image interpretation results of the pan-sharpened image. From these results, we confirmed the effectiveness of texture analysis using time-series high-resolution satellite images in grasping the damaged buildings before and immediately after the disaster and in the restoration situation 1 year after the disaster.
Highlights
On the 2016, two large earthquakes occurred continuously on April 14 and April 16 in Kumamoto prefecture, Japan (GSI, 2017)
The rubble generated from the roof and the walls is scattered, so the bright and dark pixels are adjacent around the building area, and it is assumed that the texture is not uniform
In this study, using high resolution satellite observation data observed in time series before and after the disaster, for the 2016 Kumamoto earthquake, the texture index by the GrayLevel Co-occurrence Matrix (GLCM) is calculated, and examined the grasp of the state of the building from the distribution and statistical values
Summary
On the 2016, two large earthquakes occurred continuously on April 14 and April 16 in Kumamoto prefecture, Japan (GSI, 2017). The resolution of the satellite image has been increased, and Method of object-based and pixel-based texture for extracting detailed damage information of the building and grasping the damaged area have been studied (Hussain et al, 2011; Chen et al, 2018; Suzuki et al, 2016; Horlick et al, 1973; Miura et al, 2012; Huyck et al, 2005). As a use of texture analysis for building damage in the 2016 Kumamoto earthquake, studies using aerial photographs and SAR satellite images are being conducted (Naito et al, 2018; Yamada et al., 2017). Long-term time series surveys before and after the disaster and several years after the disaster using texture analysis of satellite images have not been studied. The characteristics of the texture index were evaluated using high-resolution satellite images observed before and after the earthquake and 1 year after the earthquake
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
