A progressive morphological filter for removing nonground measurements from airborne LIDAR data

Keqi Zhang, Shu Ching Chen, Dean Whitman, Mei Ling Shyu, Jianhua Yan, Chengcui Zhang

Research output: Contribution to journalArticlepeer-review

717 Scopus citations


Recent advances in airborne light detection and ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. This technology is becoming a primary method for generating high-resolution digital terrain models (DTMs) that are essential to numerous applications such as flood modeling and landslide prediction. Airborne LIDAR systems usually return a three-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. In order to generate a DTM, measurements from nonground features such as buildings, vehicles, and vegetation have to be classified and removed. In this paper, a progressive morphological filter was developed to detect nonground LIDAR measurements. By gradually increasing the window size of the filter and using elevation difference thresholds, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Datasets from mountainous and flat urbanized areas were selected to test the progressive morphological filter. The results show that the filter can remove most of the nonground points effectively.

Original languageEnglish (US)
Pages (from-to)872-882
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number4 PART I
StatePublished - Apr 2003


  • Airborne laser altimetry
  • Digital terrain model (DTM)
  • Light detection and ranging (LIDAR) data filtering

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics
  • Computers in Earth Sciences
  • Electrical and Electronic Engineering


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