A progressive morphological filter for removing nonground measurements from airborne LIDAR data
Keqi Zhang
Shu-Ching Chen
Whitman, D.
Mei-Ling Shyu
Jianhua Yan
Chengcui Zhang
Int. Hurricane Center, Florida Int. Univ., Miami, FL, USA;
This paper appears in: Geoscience and Remote Sensing, IEEE Transactions on
Publication Date: April 2003
Volume: 41,
Issue: 4, Part 1
On page(s): 872- 882
ISSN: 0196-2892
INSPEC Accession Number: 7655612
Digital Object Identifier: 10.1109/TGRS.2003.810682
Current Version Published: 2003-06-05
Abstract
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.
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