International Journal of Geographical Information Systems · 2015 · 115 citations · 27 references
ComputingCivil EngineeringGeoinformaticsDigital Elevation ModelingGeomorphologyTerrain AnalysisCatchment AnalysisDrainage MappingLidar-based Elevation ModelingSurface DrainageTerrain Surface ModelingArtifact Detection In Digital Elevation ModelsCatchment MorphometryDamsLidar Data PreprocessingLidar Data ProcessingLidar-based Drainage AnalysisLidar-based Terrain AnalysisLidar-based Terrain Modeling
The detailed topographic information contained in light detection and ranging (LiDAR) digital elevation models (DEMs) can present significant challenges for modelling surface drainage patterns. These data frequently represent anthropogenic infrastructure, such as road embankments and drainage ditches. While LiDAR DEMs can improve estimates of catchment boundaries and surface flow paths, modelling efforts are often confounded difficulties associated with incomplete representation of infrastructure. The inability of DEMs to represent embankment underpasses (e.g. bridges, culverts) and the problems with existing automated techniques for dealing with these problems can lead to unsatisfactory results. This is often dealt with by manually modifying LiDAR DEMs to incorporate the effects of embankment underpasses. This paper presents a new DEM pre-processing algorithm for removing the artefact dams created by infrastructure in sites of embankment underpasses as well as enforcing flow along drainage ditches. The application of the new algorithm to a large LiDAR DEM of a site in Southwestern Ontario, Canada, demonstrated that the least-cost breaching method used by the algorithm could reliably enforce drainage pathways while minimizing the impact to the original DEM.
27
Photogrammetric Engineering and Remote Sensing
John Nicol, B. King · UCL Discovery (University College London) · 2007 · 9.4K citations