Flood forecasts commonly require reliable input data to accurately reflect the actual situation. Although widely used in the world, the coarse digital elevation models (DEMs) from remote sensing ...often provide poor representations of the real topography due to the effects of water and mountain shadows. Remote sensing methods cannot reliably capture riverbed elevations, and fine-scale DEMs are needed. Due to the high cost of labor and material resource limitations, complete fine-scale DEMs are difficult to obtain to support flood forecasting across long reaches at sufficiently high precision. This work presents a refined three-dimensional river channel reconstruction method by considering the longitudinal and lateral topographic features of rivers to provide realistic river terrain data. The performance of this method in flood simulation is confirmed by simulating extreme flood events in the lower-670-km reach of the Jinsha River at a 30-m resolution. The numerical simulations and field measurements are quantitatively compared in terms of flood peaks and flood propagation processes. Numerical experiments further confirm that uncertainties from terrain inputs are not amplified by the hydrodynamic model when producing the final flood forecasting outputs.
Direct point-cloud visualisation is a common approach for visualising large datasets of aerial terrain LiDAR scans. However, because of the limitations of the acquisition technique, such ...visualisations often lack the desired visual appeal and quality, mostly because certain types of objects are incomplete or entirely missing (e.g., missing water surfaces, missing building walls and missing parts of the terrain). To improve the quality of direct LiDAR point-cloud rendering, we present a point-cloud processing pipeline that uses data fusion to augment the data with additional points on water surfaces, building walls and terrain through the use of vector maps of water surfaces and building outlines. In the last step of the pipeline, we also add colour information, and calculate point normals for illumination of individual points to make the final visualisation more visually appealing. We evaluate our approach on several parts of the Slovenian LiDAR dataset.
We present a linear time Real Terrain Reconstruction (RTR) framework for fixed-wing micro aerial vehicles (MAVs) in this paper. Single-shot aerial images labeled with GPS and IMU signals are acquired ...by a fixed-wing MAV in several flights. Then these images are fed into our structure from motion (SfM) processing to generate accuracy pose estimation and 3D points. RTR improves existing state of the art algorithms VisualSFM 1 in multiaspect so as to make it more suitable for large-scale terrain reconstruction from aerial imagery. Firstly, we present a novel strategy of combining signals from airborne sensors (GPS/IMU) with the traditional SfM method, which can improve speed and accuracy of pose estimation observably. Secondly, a delayed aerial triangular method is designed to reconstruct a point visible in more than two cameras with an appropriate baseline. Thirdly, we also release 5 aerial imagery datasets which contain over 15 thousands images totally with the detailed MAV pose information from airborne sensors (GPS/IMU). These resources can be used as a new benchmark to facilitate further research in the area. We test our algorithm on these aerial image sets with various settings, and show that RTR offers state of the art performance for large-scale terrain reconstructions.
Urban waterlogging is a natural disaster that occurs in developed cities globally and has inevitably become severe due to urbanization, densification, and climate change. The digital elevation model ...(DEM) is an important component of urban waterlogging risk prediction. However, previous studies generally focused on optimizing hydrological models, and there is a potential improvement in DEM by fusing remote sensing data and hydrological data. To improve the DEM accuracy of urban roads and densely built-up areas, a multisource data fusion approach (MDF-UNet) was proposed. Firstly, Fuzhou city was taken as an example, and the satellite remote sensing images, drainage network, land use, and DEM data of the study area were collected. Secondly, the U-Net model was used to identify buildings using remote sensing images. Subsequently, a multisource data fusion (MDF) method was adopted to reconstruct DEM by fusing the buildings identification results, land use, and drainage network data. Then, a coupled one-dimensional (1D) conduit drainage and two-dimensional (2D) hydrodynamic model was constructed and validated. Finally, the simulation results of the MDF-UNet approach were compared with the raw DEM data, inverse distance weighting (IDW), and MDF. The results indicated that the proposed approach greatly improved the simulation accuracy of waterlogging points by 29%, 53%, and 12% compared with the raw DEM, IDW, and MDF. Moreover, the MDF-UNet method had the smallest median value error of 0.08 m in the inundation depth simulation. The proposed method demonstrates that the credibility of the waterlogging model and simulation accuracy in roads and densely built-up areas is significantly improved, providing a reliable basis for urban waterlogging prevention and management.
Using longitudinal control lines and sparse measured cross sections with large spaces, a new method for quickly reconstructing digital terrains in natural riverways is presented. The longitudinal ...control lines in a natural riverway, mainly including the river boundaries, the thalweg, the dividing lines of floodplains and main channel, and the water edges, can be obtained by interpreting satellite images, remote sensing images or site surveys. Then, the longitudinal control lines are introduced into quadrilateral grid generation as auxiliary lines that can control longitudinal riverway trends and reflect transverse terrain changes. Then, by the equal cross-sectional area principle at the same water level, all measured cross sections are reasonably fitted. On the above basis, by virtue of the fitted cross-sectional data and the weighted distance method, the terrain interpolations along the longitudinal grid lines are conducted to obtain the elevation data of all grid nodes. Finally, according to the readable text formats of MIKE21 and SMS, the gridded digital terrain and connection information are output by computer programming to achieve good construction of the data exchange channels and fully exploit the special advantages of various software programs for digital terrain visualization and further utilization.
In the task of lunar soil collection, estimating the volume of the collected soil is an important part of the sampling control of the lander. Due to the design constraints of the lander, there is no ...additional installation position for volume measurement equipment. To fully use the sensors already installed, a collected soil volume measurement method is designed in this paper based only on a single monitoring camera. This method uses a sequence of images of the collection area captured by the camera mounted on the acquisition arm to accurately reconstruct the terrain of the collection area surface before and after soil acquisition. Additionally, bi-temporal dense point clouds are reconstructed. Based on the area of change associated with soil collection, the constructed dense point clouds are compared according to the topographic characteristics of the area to estimate the volume of soil collected. Experiments show that the method is stable and reliable and can meet the requirements of actual measurement tasks.
Tianwen-1 is the first Mars probe launched by China and the first mission in the world to successfully complete the three steps of exploration (orbiting, landing, and roving) at the one time. Based ...on the unverifiable descent images which cover the full range of the landing area, trajectory recovery and fine terrain reconstruction are important parts of the planetary exploration process. In this paper, a novel trajectory recovery and terrain reconstruction (TR-TR) algorithm employing descent images is proposed for the dual-restrained conditions: restraints of the flat terrain resulting in an unstable solution of the descent trajectory and of the parabolic descent trajectory causing low accuracy of terrain reconstruction, respectively. A landing simulation experiment on a landing field with Mars-like landform was carried out to test the robustness and feasibility of the algorithm. The experiment result showed that the horizontal error of the recovered trajectory didn’t exceed 0.397 m, and the elevation error of the reconstructed terrain was no more than 0.462 m. The algorithm successfully recovered the descent trajectory and generated high-resolution terrain products using in-orbit data of Tianwen-1, which provided effective support for the mission planning of the Zhurong rover. The analysis of the results indicated that the descent trajectory has parabolic properties. In addition, the reconstructed terrain contains abundant information and the vertical root mean square error (RMSE) of ground control points is smaller than 1.612 m. Terrain accuracy obtained by in-orbit data is lower than that obtained by field experiment. The work in this paper has made important contributions to the surveying and mapping of Tianwen-1 and has great application value.
Fast and accurate measurement of the volume of earthmoving materials is of great significance for the real-time evaluation of loader operation efficiency and the realization of autonomous operation. ...Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fill factor estimation, and it has significant theoretical research and engineering application value.
The well-balanced, positivity-preserving scheme of Audusse et al. (SIAM J Sci Comput 25(6):2050–2065,
2004
), for the solution of the Saint-Venant equations with wetting and drying, is generalised to ...an adaptive quadtree spatial discretisation. The scheme is validated using an analytical solution for the oscillation of a fluid in a parabolic container, as well as the classic Monai tsunami laboratory benchmark. An efficient database system able to dynamically reconstruct a multiscale bathymetry based on extremely large datasets is also described. This combination of methods is successfully applied to the adaptive modelling of the 2004 Indian ocean tsunami. Adaptivity is shown to significantly decrease the exponent of the power law describing computational cost as a function of spatial resolution. The new exponent is directly related to the fractal dimension of the geometrical structures characterising tsunami propagation. The implementation of the method as well as the data and scripts necessary to reproduce the results presented are freely available as part of the open-source Gerris Flow Solver framework.
•We propose an automatic expert system for 3D terrain reconstruction based in stereo vision.•It is to be applied in autonomous robotic navigation in rough, natural terrains.•The proposed expert ...system exploits the human knowledge, mapped into three modules based on image processing techniques.•Images brightness’ are automatically adjusted, one as a function of the other, by matching their histograms.•The performance of this method is verified favorably.
This paper proposes an automatic expert system for 3D terrain reconstruction and automatic intensity correction in stereo pairs of images based on histogram matching. Different applications in robotics, particularly those based on autonomous navigation in rough and natural environments, require a high-quality reconstruction of the surface. The stereo vision system is designed with a defined geometry and installed onboard a mobile robot, together with other sensors such as an Inertial Measurement Unit (IMU), necessary for sensor fusion. It is generally assumed the intensities of corresponding points in two images of a stereo pair are equal. However, this assumption is often false, even though they are acquired from a vision system composed of two identical cameras. We have also found this issue in our dataset. Because of the above undesired effects the stereo matching process is significantly affected, as many correspondence algorithms are very sensitive to these deviations in the brightness pattern, resulting in an inaccurate terrain reconstruction. The proposed expert system exploits the human knowledge which is mapped into three modules based on image processing techniques. The first one is intended for correcting intensities of the stereo pair coordinately, adjusting one as a function of the other. The second one is based in computing disparity, obtaining a set of correspondences. The last one computes a reconstruction of the terrain by reprojecting the computed points to 2D and applying a series of geometrical transformations. The performance of this method is verified favorably.
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