A robust channel network extraction method combining discrete curve evolution and the skeleton construction technique

Zheng, Xianwei; Xiong, Hanjiang; Gong, Jianya; Yue, Linwei

doi:10.1016/j.advwatres.2015.05.003

Cited by 18 publications

(12 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A small blurring on the raster will remove sharp edges from the triangulated raster, and our approach of only using dihedral angles between triangles to detect those will fail. Approaches extracting relevant feature polylines from the raster directly [45] or more complex feature polyline detection methods on meshes [46] should be explored in the future.…”

Section: Discussionmentioning

confidence: 99%

3D Simplification Methods and Large Scale Terrain Tiling

et al. 2020

View full text Add to dashboard Cite

This paper tackles the problem of generating world-scale multi-resolution triangulated irregular networks optimized for web-based visualization. Starting with a large-scale high-resolution regularly gridded terrain, we create a pyramid of triangulated irregular networks representing distinct levels of detail, where each level of detail is composed of small tiles of a fixed size. The main contribution of this paper is to redefine three different state-of-the-art 3D simplification methods to efficiently work at the tile level, thus rendering the process highly parallelizable. These modifications focus on the restriction of maintaining the vertices on the border edges of a tile that is coincident with its neighbors, at the same level of detail. We define these restrictions on the three different types of simplification algorithms (greedy insertion, edge-collapse simplification, and point set simplification); each of which imposes different assumptions on the input data. We implement at least one representative method of each type and compare both qualitatively and quantitatively on a large-scale dataset covering the European area at a resolution of 1/16 of an arc minute in the context of the European Marine Observations Data network (EMODnet) Bathymetry project. The results show that, although the simplification method designed for elevation data attains the best results in terms of mean error with respect to the original terrain, the other, more generic state-of-the-art 3D simplification techniques create a comparable error while providing different complexities for the triangle meshes.

show abstract

Section: Discussionmentioning

confidence: 99%

3D Simplification Methods and Large Scale Terrain Tiling

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Due to their simple data structure and widespread availability, DEMs have been broadly applied in scientific fields such as ecology (Kellndorfer et al 2004), agriculture (Fu and Rich 2002), and hydrological modeling (Passalacqua et al 2010, Huang et al 2014, Zheng et al 2015. There are a variety of DEM products available with different sources.…”

Section: Introductionmentioning

confidence: 99%

Fusion of multi-scale DEMs using a regularized super-resolution method

Yue

Shen

Yuan

et al. 2015

International Journal of Geographical Information Science

Self Cite

View full text Add to dashboard Cite

The digital elevation model (DEM) is a significant digital representation of a terrain surface. Although a variety of DEM products are available, they often suffer from problems varying in spatial coverage, data resolution, and accuracy. However, the multi-source DEMs often contain supplementary information, which makes it possible to produce a higher-quality DEM through blending the multi-scale data. Inspired by super-resolution (SR) methods, we propose a regularized framework for the production of high-resolution (HR) DEM data with extended coverage. To deal with the registration error and the horizontal displacement among multi-scale measurements, robust data fidelity with weighted L 1 norm is employed to measure the conformance of the reconstructed HR data to the observed data. Furthermore, a slope-based Markov random field (MRF) regularization is used as the spatial regularization. The proposed method can simultaneously handle complex terrain features, noises, and data voids. Using the proposed method, we can reconstruct a seamless DEM data with the highest resolution among the input data, and an extensive spatial coverage. The experiments confirmed the effectiveness of the proposed method under different cases.

show abstract

“…The catchment model's effectiveness depends on the algorithm that is used to delineate the SWP from DTM. For the last few decades, there have been two main approaches to develop the SWP delineation algorithm, namely i) processing the DEM elevation data in the raster form [3], [4] and ii) processing the data in contour form [5]. To demonstrate that these algorithms are able to identify the water flow path, the SWP position error indicator is often used to measure the accuracy of these SWP delineation algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image With Boundary Element Method

et al. 2022

View full text Add to dashboard Cite

It is well-known that the delineated surface water paths (SWP) from a DEM image are essential in hydrology. Both grid-based and contour-based algorithms were proposed in the literature to improve the delineated SWP position's accuracy. Compared to the grid-based algorithm, the contour-based algorithms usually give more accurate results but require higher computation resources, especially in case of the wide catchment. This paper introduces a new contour-based algorithm which is formulated with the semi-analytical solution of Laplace's partial differential equation with boundary element method. This approach allows the algorithm to determine the SWP in any direction in order to keep the delineated SWP smooth. The proposed algorithm was validated with the standard synthetic surfaces, where theoretical SWPs are known for accuracy evaluation. The obtained SWPs are more accurate than that of the popular grid-based algorithms. Moreover, the proposed algorithm requires less computation resources when considering very long contour lines. In experimentation with a real DEM image, all delineated SWPs are absolute (no broken part) when the contour interval is equal to or less than 20 meters, and the spacing between adjacent discrete elevation data is 20 meters or narrower. This algorithm helps the hydrologists estimate the catchment area, which is useful for water management in flood and drought prevention. INDEX TERMS Flow direction algorithm, Digital Elevation Model (DEM), Surface Water Path (SWP), Boundary Element Method (BEM).

show abstract

A robust channel network extraction method combining discrete curve evolution and the skeleton construction technique

Cited by 18 publications

References 45 publications

3D Simplification Methods and Large Scale Terrain Tiling

3D Simplification Methods and Large Scale Terrain Tiling

Fusion of multi-scale DEMs using a regularized super-resolution method

A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image With Boundary Element Method

Contact Info

Product

Resources

About