Ground surface modeling for stormwater
Description
Optech’s Titan laser scanning system’s point cloud data differ slightly from other laser scanning data, so that the Titan instrument simulates at up to three separate wavelengths and captures separate laser pulses from all three channels. The wavelength frequencies produced by Titan are 1 064 nm (near-infra) and 532 nm (green). These are produced with the same laser cannon, utilising beam-splitter technology. A separate laser cannon produces a wavelength of 1 550 nm, which corresponds to the wavelength of the long-wave near-infralight. Laser beams between different channels provide the ground surface with as comprehensive and consistent coverage as possible. The intensity response recorded by Titan can be made into a similar three-channel image material that is representative of traditional aerial photography. The intensity information produced by Titan is used to identify or categorise different levels of soil in an urban area.
From the laser scanning data, the ground, buildings and water were automatically classified with TerraScan software. Ground-level dots were used to create a soil surface model for drainage analysis. Buildings were removed from the ground floor model with the help of the National Land Survey of Finland’s building polygons, so that the flows do not pass through the buildings. The drainage analysis was carried out with Terrasolid’s software. TerraModeler’s tools were used to determine the course of raindrops along the surface model. The tool draws flow elements and catchment areas into a dgn file.
The laser point cloud was made into a vegetation surface model describing the height of the vegetation. This was produced by subtracting the heights of the ground model from the heights of the laser points and by interpolating the raster surface from the point heights describing the height of the vegetation. This vegetation surface model (height raster) was used in automatic classification of the target area to distinguish objects of different heights into different categories. The intensity raster was utilised in the classification of objects based on the radiation they reflect.
For the purpose of classification, a teaching material containing different target categories was first created for automatic classification in the target area by searching for map, street view and remote sensing materials in the area using different objects: field, lawn, asphalt, sand, bare soil, shallow vegetation, high vegetation and various roofing materials (several different categories). The teaching material consisted of approximately 200 observations.
The target area was then autoprinted using Trimble’s eCognition image analysis software to divide the image into areas with homogeneous tone values (micro patterns). By utilising teaching material and eCognition’s guided classification, each microfiche was classified into one of the categories found in the teaching material. For the purposes of the drainage analysis, the classification was simplified to include asphalt and sand areas as impermeable. The other classes were defined as a permeable class.
From the flow areas and lines analysed with Terrasolid, the smallest areas and streams were filtered out. It was then selected from the flow ranges and lines where the lowest point was in the impermeable area based on automatic classification. This made it possible to find places where there may be stormwater problems because the water flowing to the target cannot be absorbed into the soil.
Resources
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https://www.avoindata.fi/data/dataset/4a03ec97-2fee-49e3-bafc-6910f06217a4/resource/5c360d36-0f98-4733-a90f-8a70c022ca0d |
Tags
- hulevesi
- maanpinta
- mallinnus