Classification of landcover from combined LiDAR and orthophotos using support vector machine

• Main Authors: Pula, Rolando A., Concepcion, Ronnie, Ilagan, Lorena, Tobias, Rogelio Ruzcko
• Format: text
• Published: Animo Repository 2019
• Subjects: Land cover—Classification; Support vector machines; Orthophotography; Digital elevation models
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2704
• Institution: De La Salle University

© 2019 IEEE. The study is based on the Landcover classification from combined light detection and ranging (LiDAR) data and orthophotos. Five land classes were extracted namely: barren, build up, low vegetation, mango, and non-agricultural trees. Support vector machine (SVM) was the algorithm used fo...