REVISED PROGRESSIVE MORPHOLOGICAL METHOD FOR GROUND POINT CLASSIFICATION OF AIRBORNE LIDAR DATA

Authors

  • Mohd Radhie Mohd Salleh TropicalMap Research Group, Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Muhammad Zulkarnain Abd Rahman TropicalMap Research Group, Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Zamri Ismail Photogrammetry & Laser Scanning Research Group, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Faisal Abdul Khanan Photogrammetry & Laser Scanning Research Group, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Asraff Asmadi TropicalMap Research Group, Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/ijbes.v6.n1-2.380

Keywords:

Airborne LiDAR, LiDAR Filtering, Progressive Morphology, Slope, Tropical Area

Abstract

Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain information over different scales of area. Inevitably, filtering the non-ground returns is the major step of digital terrain model (DTM) generation and this step poses the greatest challenge especially for tropical forest environment which consists of steep undulating terrain and mostly covered by a relatively thick canopy density. The aim of this research is to assess the performance of the Progressive Morphological (PM) algorithm after the implementation of local slope value in the ground filtering process. The improvement on the PM filtering method was done by employing local slope values obtained either using initial filtering of airborne LiDAR data or ground survey data. The filtering process has been performed with recursive mode and it stops after the results of the filtering does not show any improvement and the DTM error larger than the previous iteration. The revised PM filtering method has decreasing pattern of DTM error with increasing filtering iterations with minimum ±0.520 m of RMSE value. The results also suggest that spatially distributed slope value applied in PM filtering algorithm either from LiDAR ground points or ground survey data is capable in preserving discontinuities of terrain and correctly remove non-terrain points especially in steep area.

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Published

2019-04-01

How to Cite

Mohd Salleh, M. R., Abd Rahman, M. Z., Ismail, Z., Abdul Khanan, M. F., & Asmadi, M. A. (2019). REVISED PROGRESSIVE MORPHOLOGICAL METHOD FOR GROUND POINT CLASSIFICATION OF AIRBORNE LIDAR DATA. International Journal of Built Environment and Sustainability, 6(1-2), 31–38. https://doi.org/10.11113/ijbes.v6.n1-2.380

Issue

Vol. 6 No. 1-2 (2019): Special issue of the 7th International Graduate Conference on Engineering, Science And Humanities (IGCESH)

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