NOISE REDUCTION IN CONTOUR LINES AND SLOPE MAPS FROM MEDIUM/HIGH-DENSITY LIDAR DATA

J. Santamaría-Peña, Elena Palacios-Ruiz, Teresa Santamaría-Palacios
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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.
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基于中/高密度激光雷达数据的等高线和坡度图降噪研究
使用中/高密度激光雷达(光探测和测距)数据进行陆地建模和DTM(数字地形模型)正变得越来越普遍。这种程度的细节很难用其他手段或材料来实现。然而,获得的激光雷达点的水平和垂直几何精度虽然很高,但并不均匀。水平精度可以达到30-50厘米左右,而垂直精度很少大于10-15厘米。激光雷达飞行的结果是,即使地形平坦,云点彼此非常接近(30-60厘米),高度变化显著。这使得从这些激光雷达数据中得到的三角网模型TIN (triangulation不规则网络)变得特别混乱。由于等高线是由这种三角化模型直接生成的,因此等高线的外观显示出过多的噪声,过度断裂和快速闭合。如何在不降低精度的情况下获得平滑的轮廓度是地形模型软件面临的一个挑战。此外,从激光雷达数据中获得的三角模型是未来土地坡度图的基础。由于上一段所解释的原因,这些由高密度或中密度激光雷达点云产生的斜率是特别不均匀的。通过减少激光雷达数据的自然噪声来实现均匀性和对现实的更大调整是另一个额外的挑战。本文提出了高密度(约8点/m2)和中密度(约2点/m2)激光雷达数据在等高线和地形坡度图生成过程中存在的噪声过大问题,并提出了降低噪声的解决方案。所有这些都是在管理TIN模型和GIS(地理信息系统)的特定软件领域,并适应这些方案提出的替代方案。
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