With increasing widespread use of three-dimensional data, the demand for simplified data acquisition is also increasing. The range camera, which is a simplified sensor, can acquire a dense-range image in a single shot ; however, its measuring coverage is narrow and its measuring accuracy is limited. We had overcome the former drawback by registering sequential range images. This method, however, assumes that the point cloud is error-free. In this paper, we have developed an integration method for sequential range images with error adjustment of the point cloud. The proposed method consists of ICP (Iterative Closest Point) algorithm and self-calibration bundle adjustment. The ICP algorithm is considered an initial specification for the bundle adjustment. By applying the bundle adjustment, coordinates of the point cloud are modified and the camera poses are updated. Through experimentation on real data, the significance of the proposed method has been confirmed.
We can measure depth of rivers quite efficiently by using ALB (Airborne Laser Bathymetry) technology. But in order to use ALB we must fly very low at 400 meters by airplane. So ALB is not usable anywhere. In this study, we developed a method for estimating the area where we can use ALB technology under topographical restriction. We simulated the applicable river area managed by the national government by this method and got the result that ALB can apply to 31% of the national river area.
In previous studies, it has been found that total coliform is highly correlated with building data. After classifying building data in the basins of Oita and Ono Rivers according to its use, we analyze and evaluate correlations between the classified building data and total coliform in June. As a result of the analysis, we found that total coliform is highly correlated with the commercial and educational welfare facilities.