Geometric road runoff estimation from laser mobile mapping data
| Autor: | Higinio González-Jorge, Jinhu Wang, Roderik Lindenbergh, Massimo Menenti, Pedro Arias-Sanchez |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
lcsh:Applied optics. Photonics
Water flow lcsh:T D8 algorithm Mobile Laser Scanning Point cloud lcsh:TA1501-1820 Landslide Grid lcsh:Technology Point Cloud Data lcsh:TA1-2040 Snowmelt Environmental science Catchments Surface runoff Gradient descent lcsh:Engineering (General). Civil engineering (General) Road runoff Road Engineering Remote sensing Mobile mapping |
| Zdroj: | ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(5) ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol II-5, Pp 385-391 (2014) |
| ISSN: | 2194-9042 2194-9050 |
| Popis: | Mountain roads are the lifelines of remote areas but are often situated in complicated settings and prone to landslides, rock fall, avalanches and damages due to surface water runoff. The impact and likelihood of these types of hazards can be partly assessed by a detailed geometric analysis of the road environment. Field measurements in remote areas are expensive however. A possible solution is the use of a Laser Mobile Mapping System (LMMS) which, at high measuring rate, captures dense and accurate point clouds. This paper presents an automatic approach for the delineation of both the direct environment of a road and the road itself into local catchments starting from a LMMS point cloud. The results enable a user to assess where on the road most water from the surroundings will assemble, and how water will flow over the road after e.g. heavy snow melt or rainfall. To arrive at these results the following steps are performed. First outliers are removed and point cloud data is gridded at a uniform width. Local surface normal and gradient of each grid point are determined. The relative smoothness of the road is used as a criterion to identify the road’s outlines. The local gradients are input for running the so-called D8 method, which simply exploits that surface water follows the direction of steepest descent. This method first enables the identification of sinks on the roadside, i.e. the locations where water flow accumulates and potentially enters the road. Moreover, the method divides the road’s direct neighbourhood into catchments, each consisting of all grid cells having runoff to the same sink. In addition the method is used to analyse the surface flow over the road’s surface. The new method is demonstrated on a piece of 153 meters long Galician mountain road as sampled by LMMS data. |
| Databáze: | OpenAIRE |
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