POSITIONAL ACCURACY ASSESSMENT OF FEATURES USING LIDAR POINT CLOUD

Abstract. Nowadays, Light Detection and Ranging (LiDAR) data acquisition technology is gaining popularity due to its accuracy, precision, and rapid data collection. In recent years, many applications have demanded 3-D models and 3-D mapping for fly-through views of cities. LiDAR data is used to map topographic features as well as the height and density of high-rise objects, such as trees and buildings, on the earth's surface. Although there are numerous traditional surveying and space-based technologies existing to determine the elevation or height of any object are time-consuming, inaccurate, and require additional effort. Therefore, the present study focused on developing a large-scale 3D map and accuracy assessment for existing high-rise features in the study area using a Terrestrial Laser Scanner (TLS). Further, LiDAR point cloud data has been used to estimate the position and elevation of the building. It can acquire data anytime, i.e., day and night, and collects more than 1.5 million points per second. The FARO Scene software has been used to process the data, and the processed data is then automatically registered and verified. The point cloud data's overall registration RMSE error is 36 mm. This file with an extension *.LAS format contains the positional coordinates of the features.

The approach provided here for positional accuracy of features with improved accuracy will be helpful for identifying and monitoring the shift and deformations in the buildings and other features. It may also be used for site analysis, planning, and building information modeling.