Live Extraction of Curvilinear Structures From Lidar Raw Data

Abstract

Abstract. In this paper, a general framework is proposed for live extraction of curvilinear structures such as roads or ridges from airborne LiDAR raw data, in the scope of present and past man-environment interaction studies. Unlike most approaches in literature, classified ground points are directly processed here, rather than derived products such as digital terrain models (DTM). This allows to detect possible lacks of ground points due to LiDAR signal occlusions caused by dense coniferous canopies. An efficient and simple solution based on discrete geometry tools is described for supervised context in which the user just indicates where the extraction should take place. Fast response times are required to ensure a good man-system interaction.The framework performance is first evaluated on the example of the extraction of forest roads in a mountainous area, as these objects are well marked in the DTM and hence provide some kind of ground truth. Good execution time and accuracy level are reported. Then this framework is applied to the detection of prominent curvilinear structures, which are much more diffuse objects, but of greater interest than roads in the scope of the present project. Achieved results show high potential of the proposed approach to help archaeologists and geomorphologists in finding areas of interest for future prospection using LiDAR data.

Interactive Extraction of Linear Structures From Lidar Rawdata for Archaeomorphological Structure Prospection

“…Based on the extraction framework algorithms proposed in (Even and Ngo, 2020), a new tool called ILSD (for Interactive Linear Structure Detector), dedicated to archaeological prospection purposes, has been developed and is available as an open source software. It allows to extract and analyze linear structures (ridge or hollow) by detecting and tracking their cross profiles in the 3D ground point cloud of the LiDAR data set.…”

“…Compared to the method of (Even and Ngo, 2020), the ridge model has been improved to better suit to the different archaeological or geomorphological structures addressed in this work and to provide more reliable geometric estimations. Moreover, the extraction of hollow structures has also been added.…”

“…The principle of the extraction framework is just summarized in the following section. More details can be found in (Even and Ngo, 2020). The improved ridge model is then introduced in details.…”

“…The bump lies on a straight baseline, and the area of the polygon closed by the bump surface points and the baseline can be measured. Additionally to the model proposed in (Even and Ngo, 2020), the local terrain trend may be detected on both sides of the bump in order to get more accurate detection and measures, and the bump center is computed with more accuracy. Hollow structure detection is also implemented.…”

“…It allows the supervised extraction of linear structures (ridge or hollow) directly from 3D surface point profiles, and a detailed analysis of their cross section along their run (see Figure 1). This tool implements a recent framework (Even and Ngo, 2020), refered to as the extraction framework in the following, relying on digital geometry algorithms to efficiently process raw ground points and get rid of DTM approximations. The performance of this framework was mostly evaluated on forest roads extraction, that is of minor interest for archaeologists.…”