Filtering Airborne Laser Scanner Data
Filtering the airborne laser scanner data is challenging due to the complex distribution of objects on Earth’s surface and it is still in development stage. This problem has been investigated so far with varieties of algorithms, but they suffer from different magnitudes of
drawbacks. This study proposed a new and improved hybrid method based on multi-resolution analysis. Wavelet was adopted in this multi-resolution clustering approach. It enabled the classification of objects based on their size and the efficiency to filter out unwanted information at a specific
resolution, and the proposed algorithm is named the ALSwave (Airborne Laser Scanner Wavelet) method. ALSwave has been tested on two data sets acquired over the urban areas of Tokyo, Japan and Stuttgart, Germany. The results showed a well-filtered, bare earth surface coupled with
acceptable computational time. The accuracy assessment was carried out by comparison between the filtered bare earth surface by ALSwave and the manually filtered surface. The Root Mean Square Error (RMSE) follows a linear relationship with respect to terrain slope. This wavelet-based
approach has opened a new way to filter the raw laser data that subsequently generates fast and more accurate digital terrain models.
Document Type: Research Article
Publication date: 01 November 2004
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
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