Abstract
The use of medium/high-density LIDAR (Light Detection And Ranging) data for land modelling and DTM (Digital TerrainModel) is becoming more widespread. This level of detail is difficult to achieve with other means or materials. However,the horizontal and vertical geometric accuracy of the LIDAR points obtained, although high, is not homogeneous.Horizontally you can reach precisions around 30-50 cm, while the vertical precision is rarely greater than 10-15 cm. Theresult of LIDAR flights, are clouds of points very close to each other (30-60 cm) with significant elevation variations, evenif the terrain is flat. And this makes the triangulated models TIN (Triangulated Irregular Network) obtained from such LIDARdata especially chaotic. Since contour lines are generated directly from such triangulated models, their appearance showsexcessive noise, with excessively broken and rapidly closed on themselves. Getting smoothed contour liness, withoutdecreasing accuracy, is a challenge for terrain model software. In addition, triangulated models obtained from LIDAR dataare the basis for future slope maps of the land. And for the same reason explained in the previous paragraph, these slopemaps generated from high or medium density LIDAR point clouds are especially heterogeneous. Achieving uniformity andgreater adjustment to reality by reducing the natural noise of LIDAR data is another added challenge. In this paper, theproblem of excessive noise from LIDAR data of high (around 8 points/m2) and medium density (around 2 points/m2) in thegeneration of contour lines and terrain slope maps is raised and solutions are proposed to reduce this noise. All this, in thearea of specific software for the management of TIN models and GIS (Geographic Information System) and adapting thealternatives proposed by these programmes.
Highlights
The currently existing problem regarding the use of médium/high density LIDAR data for the generation of digital terrain models (DTM) will be described (Sharma et al 2021) and the obtaining of contour lines and slope maps drawn from them
The LIDAR flight had an average density of 2 points/m2, which requires handling a total of approximately eight million points
As stated in the previous section, we will work with a LIDAR flight sheet (Plan Nacional de Ortofotografía Aérea, PNOA) for 2016, which covers an area of 4 km2 and has an initial point density of 2 points/m2
Summary
The currently existing problem regarding the use of médium/high density LIDAR data for the generation of DTM will be described (Sharma et al 2021) and the obtaining of contour lines and slope maps drawn from them.Someone may have the mistaken feeling that a higher resolution of the lidar data is, better digital models will be obtained and the more accurate the contour lines extracted from them will be. For the dynamic management of the model in CIVIL3D®, three simplification processes of the point cloud have been previously carried out, reducing the number of points to 1.470.941 points and generating a triangulation of approximately two million triangles (Fig. 2). In the detail of the previous figure it is observed how the generated contour lines are excessively sinuous and very broken. The explanation for this phenomenon should be sought precisely in the excessive variability of the vertical precision of the LIDAR points (López-Fernández et al 2017), which will rarely be greater than 10 cm or 15 cm and in the existence of very close triangulated points. The explanation for this phenomenon should be sought precisely in the excessive variability of the vertical precision of the LIDAR points (López-Fernández et al 2017), which will rarely be greater than 10 cm or 15 cm and in the existence of very close triangulated points. (between 40 and 60 cm) in point clouds between 2-6 points/m2
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Topics from this Paper
Light Detection And Ranging Data
Light Detection And Ranging
Triangulated Irregular Network
Light Detection And Ranging Point
Triangulated Models
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