Abstract
Automatic ground filtering for Light Detection and Ranging (LIDAR) data is a critical process for Digital Terrain Model and three-dimensional urban model generation. Various methods have been proposed in literature to separate ground from non-ground, but sometimes problem has been occurred due to the similar characteristics possessed by ground and non-ground objects. The proposed approach in this paper is based on neighborhood based approach. Hierarchy of preprocessing is done for LIDAR data using various essential tools. K-D tree is used to distinguish the bare ground and non-ground objects using nearest neighbor search. Experimental results show the effectiveness of the proposed approach.
Highlights
lightweight detection and travel (LiDAR) (Light Detection and Ranging) could be a remote sensing technique supported optical device technology
Mobile lightweight detection and travel (LiDAR) has bit by bit become a thought tool for aggregation elevation info of surface targets by scheming the time of flight taken for optical device pulse travel between a measuring system device and a target scene
Our goal is to develop a stronger ground filtering algorithmic program to facilitate DTM creation
Summary
LiDAR (Light Detection and Ranging) could be a remote sensing technique supported optical device technology. It measures the period of time of the emitted optical device pulses to work out the space between the device and the ground. Mobile lightweight detection and travel (LiDAR) has bit by bit become a thought tool for aggregation elevation info of surface targets by scheming the time of flight taken for optical device pulse travel between a measuring system device and a target scene. Measuring system has 2 major blessings over photogrammetric systems: [1] the acquisition of vertical info over an oversized space is additional cost-effective; and [2] there are fewer necessities for information preprocessing The raw measuring system information contains tremendous points came from numerous objects, like buildings, trees, vehicles etc. measuring system has 2 major blessings over photogrammetric systems: [1] the acquisition of vertical info over an oversized space is additional cost-effective; and [2] there are fewer necessities for information preprocessing
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