Random Forest Machine Learning Technique for Automatic Vegetation Detection and Modelling in LiDAR Data

 

Abstract

Machine learning techniques have gained a distinguished position in the automatic processing of Light Detection and Ranging (LiDAR) data area. They represent the actual research topic in the remote sensing domain. Indeed, this paper presents one method of supervised machine learning, which is called Random Forest. This algorithm is discussed, and their primary applications in automatic vegetation extraction and modelling in the LiDAR data area are presented here.

 

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