River administration facilities such as levees and river walls play a major role in preventing flooding due to heavy rain. The forms of such facilities must be constantly monitored for alteration due to rain and running water, and limited human resources and budgets make it necessary to efficiently maintain river administration facilities. It is necessary to allow for immediate and accurate reference to accumulated inspection data. In current maintenance work, river administration facilities are shown on two-dimensional maps, which are not suitable for grasping river forms. Using three-dimensional data will thus improve the efficiency of operations and maintenance. In river maintenance, it is necessary to construct an environment that manages three-dimensional data and maintenance information.
This study proposes a maintenance management for river facilities that uses three-dimensional data to make operation and maintenance more efficient. Three-dimensional data use to visualize river facility deformation. And the management has characteristics that visualize information about river management at any point in the three-dimensional data. The three-dimensional data is generated by photogrammetry using a camera on an Unmanned Aerial Vehicle (UAV). This study evaluates the accuracy of point cloud data generated by photogrammetry. We investigate the influences of error factors and their occurrence conditions in photogrammetry, and proposes a measurement method for civil infrastructure management.
A DJI Phantom3 Professional UAV was used to measure the river administration facility. Operators pointed the camera downward and took videos of the river from above. Photographs were extracted from the video for Structure from Motion (SfM). The wrap rate of photographs affects the data accuracy. The UAV was flown at a constant speed and lateral movement of about 5 meters to maintain a wrap rate of 80%. SfM is a range-imaging technique that constructs three-dimensional data of an object from images taken from various angles.
To evaluate the accuracy of point cloud data, there were two experiments. The target of these experiments is the accuracy of the point cloud corresponding to flight height, number of localization points, number of benchmark points, and the function of PhotoScan software. The accuracy is validated using RMSE (Root Mean Squared Error). RMSE is calculated using the true coordinate measured by GNSS (Pentax G3100-R2B) and point clouds. The point clouds were generated on the plane ground and the river facilities. The RMSEs of point clouds of river facilities are 0.115m at 20m height and 0.120m at 25m height on the viewpoint of xy two-dimensional plane. The RMSE of elevation is 0.152m. According to these results, the point clouds of UAV photogrammetry have the accuracy for fulfilling the standard deviation requirement 0.12m for map information level 500 defined by Ministry land, infrastructure, transportation and tourism of Japan. The point clouds have the capability for river management use.
