LINEAR REGRESSION AND LINES INTERSECTING AS A METHOD OF EXTRACTING PUNCTUAL ENTITIES IN A LIDAR POINT CLOUD

• Autor(a) principal: Martins, Marlo Antonio Ribeiro
• Data de Publicação: 2022
• Outros Autores: Mitishita, Edson Aparecido
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Boletim de Ciências Geodésicas
• Texto Completo: https://revistas.ufpr.br/bcg/article/view/84199
• topic: Geociências, Ciências da Terra; Point Cloud LiDAR; Linear Regression; Lines Intersection; PEC-PCD.

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.