Random Forest Machine Learning Technique for Automatic Vegetation Detection and Modelling in LiDAR Data
Fayez Tarsha Kurdi
2021International Journal of Environmental Sciences & Natural Resources24 citationsDOIOpen Access PDF
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.
Topics & Concepts
LidarRandom forestVegetation (pathology)Remote sensingEnvironmental scienceComputer scienceArtificial intelligenceGeographyPathologyMedicineRemote Sensing and LiDAR ApplicationsRemote Sensing in AgricultureSpecies Distribution and Climate Change