Dr. Yoshiyuki Yamamoto Profile

Dr. Yoshiyuki Yamamoto

at Aichi Institute of Technology

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Proceedings Article | 21 November 2012 Paper

Detection of damaged buildings using GeoEye-1 imagery and airborne lidar data: A case study on the 2011 Tohoku earthquake

Y. Yamamoto, T. Asaka, S. Aoyama, K. Iwashita, K. Kudou

Proceedings Volume 8524, 852412 (2012) https://doi.org/10.1117/12.977355

KEYWORDS: Buildings, LIDAR, Satellites, Earthquakes, Spatial resolution, Satellite imaging, Detection and tracking algorithms, Remote sensing, Earth observing sensors, Data conversion

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This paper presents a methodology that utilizes high-resolution optical satellite imagery, specifically GeoEye-1, and airborne lidar data to detect disaster-related damaged buildings in order to conduct a case study on the 2011 Tohoku earthquake. The methodology is based on change detection algorithms used in the field of image processing for remote sensing. Specifically, we examine the use of the image algebra change detection algorithm. This algorithm identifies the amount of change between two rectified images by band rationing or image differencing. On the other hand, it seems that the results calculated are different depending on the calculation method used because the data type of satellite data is different from that of the airborne lidar data. In this research, we propose three methods for creating a dataset used to detect damaged buildings: the Difference method, the Ratio method, and the Normalized Difference method, which are simply referred to as the D-method, R-method, and ND-method, respectively. The D-method is based on the difference in the value of the post-event imagery compared to that of the pre-event imagery. The R-method is based on the quotient of dividing the value of the pre-event imagery by that of the post-event imagery. The ND-method uses a calculation formula that is similar to that used by the Normalized Difference Vegetation Index (NDVI). The experimental results indicate that the dataset created using the ND-method has a higher sensitivity in the detection of damaged buildings than that of other methods.

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