Volume XLII-2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 901-907, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-901-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 901-907, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-901-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 May 2018

30 May 2018

CLASSIFICATION OF DUAL-WAVELENGTH AIRBORNE LASER SCANNING POINT CLOUD BASED ON THE RADIOMETRIC PROPERTIES OF THE OBJECTS

M. Pilarska M. Pilarska
  • Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland

Keywords: airborne laser scanning, LiDAR, multispectral laser scanning, classification, OPALS, GNDVI

Abstract. Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.