[M-IS04] Extreme Weather and Water-Related Disasters in Asia

[MIS04-P06] Simplify and Accelerate the Process of Constructing 3D Model of Active Clouds Using Ground and Satellite Images.

*長澤 稔幸¹、高橋 幸弘²、久保田 尚之³ (1.沼津工業高等専門学校、2.北海道大学・大学院理学院・宇宙理学専攻、3.北海道大学)

キーワード：アイウォール、ステレオ写真測量、集中豪雨、台風、雲の鉛直分布

Typhoons and torrential rains are weather phenomena that cause much damage and casualties. In addition, their intensity may increase due to global warming. Because of this, there is a need to accurately measure their intensity and mitigate the risks caused by them. Currently, the method developed by Dvorak is the predominant method. The Dvorak method qualitatively estimates the intensity of typhoons based on satellite images of typhoon clouds taken from above. Therefore, recent studies have focused on quantitative information such as cloud-top altitude and three-dimensional structure of eyewalls of typhoons. Among them, stereo photogrammetry using microsatellites is one of the effective methods to measure the vertical distribution of clouds. The vertical distribution of cumulonimbus clouds is also effective in predicting torrential rainfall. Stereophotogrammetry is a technique and time-consuming method to measure the vertical distribution of clouds. However, stereophotogrammetry is time-consuming and requires specialized skills. In this study, we were able to simplify and speed up the procedure to construct a 3D model by implementing a program to construct the operation using images taken from the ground or satellite images. The ground image used in this study was taken of clouds over Tokyo on August 12, 2023. In this case, the location information of the same structure in multiple images was used as a reference to correct the camera orientation estimation. In addition, we implemented a function to determine the altitude range of cumulonimbus clouds using the altitude information from a model constructed from ground structure images. Satellite images were taken of Typhoon No. 16 (Mindulle) on September 29, 2021. Furthermore, a function was implemented to obtain the altitude information of the model at a specified latitude or longitude and display a cross-sectional view so that the structure of clouds and cumulonimbus clouds around the eyewall could be determined.