Abstract
Abstract: The characteristics of data points obtained by laser scanning (LiDAR) and images have been considered complementary in the field of photogrammetric applications, and research to improve their integrated use have recently intensified. This study aim to verify the performance of determining punctual entities in a LiDAR point cloud using linear regression and intersecting lines obtained from buildings with square rooftop containing four planes (hip roof), as well as compare punctual entities three-dimensional coordinates determined by planes intersection. Our results show that the proposed method was more accurate in determining three-dimensional coordinates than plan intersection method. The obtained coordinates were evaluated and framed into the map accuracy standard for digital cartographic products (PEC-PCD), besides being analyzed for trend and precision. Accuracy analysis results frame punctual entities three-dimensional coordinates into the 1/2,000 or lower scale for Class A of PEC-PCD.
Highlights
Research to improve efficiency, reliability, and reduce the costs of mapping techniques and procedures has always been in several researches
The results obtained by extracting punctual entities using linear regression and lines intersection will be thoroughly presented and discussed
3.1 Results Obtained with Linear Regression and Lines Intersection
Summary
Reliability, and reduce the costs of mapping techniques and procedures has always been in several researches. Indirect georeferencing has traditionally been used to integrate photogrammetric and LiDAR datasets Applying this approach while using LiDAR data as a source of positional information requires all primitive geometries (points, lines, and areas) to be extracted, as data sourced from this technology does not directly display these primitives. Most photogrammetric surveys nowadays integrate GNSS/INS to calculate camera position and orientation at the exposure time and are carried out simultaneously to LiDAR Such procedure can acquire both LiDAR and photogrammetric dataset within the same mapping system, whether geodesic or not. According to Kersting (2011), photogrammetric calibration is often performed independently of the LiDAR system, and direct georeferencing depends on local flight conditions, as variations in temperature and atmospheric pressure conditions can change the camera position and orientation in relation to the Inertial Measurement Unit Geometric entities such as points, lines, and areas are essential for calibrating both photogrammetric and LiDAR systems. This article presents the study conducted for extracting 3D coordinates from punctual entities of LiDAR point clouds using linear regression and lines intersection, and for comparing results obtained by different traditional procedures, such as planes intersection (Costa, Mitishita and Martins, 2018) and conventional topographic surveys
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