Rainfall intensity estimations based on degradation characteristics of images taken with commercial cameras

Abstract

Camera-based rainfall observation is a useful technology that contributes to the densification of rainfall observation networks because it can measure rainfall with high spatiotemporal resolution and low cost. To verify the applicability of existing theories, such as computer vision and meteorological studies, to static weather effects caused by rain in outdoor photography systems, this study proposed relational equations representing the relationship between image information, rainfall intensity, and scene depth by linking the theoretically derived rainfall intensity with a technique proposed in the computer vision field for removing static weather effects. This study also proposed a method for estimating rainfall intensity from images using those relational equations. Because the method uses only the camera image taken of the background over a certain distance and background scene depth information, it is a highly versatile and accessible method. The proposed equations and the method for estimating rainfall intensity from images were applied to outdoor images taken by commercial interval cameras at the observation site in a mountainous watershed in Japan. It was confirmed that transmission calculated from the image information decreases exponentially according to the increase in rainfall intensity and scene depth, as assumed in the proposed equations. Furthermore, rainfall intensity can be estimated from the image using the proposed relational equations. On the other hand, the calculated extinction coefficient tended to be overestimated at small scene depth. Although there are several problems at present that need to be resolved for the technology proposed in this study, this technology has the potential to facilitate the development of a camera-based rainfall observation technology that is accurate, robust, versatile, and accessible.