A mobile light detecting and ranging (LiDAR) system is used to provide point cloud datasets as a topographic base for runoff studies. The point clouds are rasterized to evaluate road runoff using the D8 algorithm. Gaussian noise is artificially induced in the point cloud to simulate inaccuracies in geopositioning and determine its influence in the evaluation of runoff direction. Accuracy in the determination of flow direction decreases with the increase of Gaussian noise. Accuracy also decreases with the decrease of the cell size of the raster dataset. Flow direction shows inaccuracies up to 47 deg with a cell resolution of 0.5 m and Gaussian noise of 0.15 m (standard deviation). On the other hand, cell resolutions of 5 m show a maximum difference of 15 deg with the same noise.
A low-cost image orthorectification tool based on the utilization of compact cameras and scale bars is developed to obtain the main geometric parameters of masonry bridges for inventory and routine inspection purposes. The technique is validated in three different bridges by comparison with laser scanning data. The surveying process is very delicate and must make a balance between working distance and angle. Three different cameras are used in the study to establish the relationship between the error and the camera model. Results depict nondependence in error between the length of the bridge element, the type of bridge, and the type of element. Error values for all the cameras are below 4 percent (95 percent of the data). A compact Canon camera, the model with the best technical specifications, shows an error level ranging from 0.5 to 1.5 percent.
A low cost physical artifact with traceability to the national standard - meter is used for the metrological comparison of two terrestrial laser scanning systems: Riegl LMS Z390i and Trimble GX. The artifact is based on five spheres equidistantly situated and seven cubes of different dimensions. Accuracy and repeatability are evaluated using least squares fitting (LSF) and random sample consensus algorithms, for the study case of the spheres, and plane LSF and statistical analysis for the cubes. The horizontal resolution is evaluated using a modulated transfer function approach and the vertical one with the accuracy and repeatability data along Z axis. The Trimble system shows better results for all parameters, artifact parts, and algorithms under study.
A low-cost mechanical artifact is developed for the metrological verification of photogrammetric measurement systems. It is mainly composed of five delrin spheres and seven cubes manufactured in different sizes. A set of circular targets are fixed on these elements to perform the photogrammetric restitution. The artifact is used in order to compare three photogrammetric systems defined by three different cameras (Canon 5D with 14-mm lens, Nikon D200 with 20-mm lens, and Jai BB500GE with 8-mm lens). Photomodeler Pro and Matlab software are used for the data processing. The precision of the systems is evaluated using the standard deviation of the geometric coordinates calculated from the restitution of the circular targets. The accuracy is calculated using two different procedures: one of them uses the distance between the center of the spheres and the other uses the distance between the faces of the cubes. The comparison between the photogrammetric systems and their associated calibration files reveals that the Jai camera produces the best results in terms of precision and accuracy, while the Canon camera produces the poorest ones. The bad results from the Canon system are primarily related to the low quality of the calibration procedure.