Application of generative adversarial network: GAN to disaster damage monitoring

Yushin Nakaoka; Kohei Arai; Osamu Fukuda; Nobuhiko Yamaguchi; Wen Liang Yeoh; Hiroshi Okumura

doi:10.1117/12.2679974

19 October 2023 Application of generative adversarial network: GAN to disaster damage monitoring

Yushin Nakaoka, Kohei Arai, Osamu Fukuda, Nobuhiko Yamaguchi, Wen Liang Yeoh, Hiroshi Okumura

Proceedings Volume 12733, Image and Signal Processing for Remote Sensing XXIX; 127330Z (2023) https://doi.org/10.1117/12.2679974
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Conference Poster

Abstract

In recent years, natural disasters have caused serious damage. In particular, landslides caused by earthquakes are damaging. However, it is difficult to predict when and where natural disasters will occur. Therefore, this study was conducted on early detection of landslides. SAR (Synthetic Aperture Radar) is a remote sensing technology. It uses microwaves and can observe day and night in all weather conditions. But this SAR data is a grayscale image, which is difficult to analyze without specialized knowledge. Therefore, we decided to use machine learning to detect changes in disasters that appear in SAR data. There are two machine learning models called pix2pix and pix2pixHD for image transformation. The objective of this study is to detect changes of surface by transforming pseudo-optical images from SAR data using machine learning. Two machine learning models were used for training, with test images and actual disaster data input. Simple terrain, such as forests only, was highly accurate, but complex terrain was difficult to generate. About actual disaster data, something like disaster-induced changes appeared in the converted images. However, we found it difficult to distinguish bare area from grassland in the output images. In the future, it is necessary to consider the combination of data to be used for learning.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yushin Nakaoka, Kohei Arai, Osamu Fukuda, Nobuhiko Yamaguchi, Wen Liang Yeoh, and Hiroshi Okumura "Application of generative adversarial network: GAN to disaster damage monitoring", Proc. SPIE 12733, Image and Signal Processing for Remote Sensing XXIX, 127330Z (19 October 2023); https://doi.org/10.1117/12.2679974

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