Classification Airbrone LiDAR Point cloud Data

Abstract

Land cover classification information plays a very important role in various applications. Airborne Light detection and Ranging (LiDAR) data is widely used in remote sensing application for the classification of land cover. The present study presents a Spatial classification method using Terrasoild macros . The data used in this study are a LiDAR point cloud data with the wavelength of green:532nm, near infrared:1064nm and mid-infrared-1550nm and High Resolution RGB data. The classification is carried in TERRASCAN Module with twelve land cover classes. The classification accuracies were assessed using high resolution RGB data. From the results it is concluded that the LiDAR data classification with overall accuracy and kappa coefficient 85.2% and 0.7562.