Adaptive multiresolutional algorithm for high-precision forest floor DTM generation

Adaptive multiresolutional algorithm for high-precision forest floor DTM generation This paper focuses on an adaptive multi-resolutional algorithm for generating forest floor digital elevation models by processing the three dimensional data acquired by the laser scanner. The adaptivity of our algorithm ensures that it can be used successfully in flat, hilly, and mountainous terrain and deliver accurate results. A large set of GPS ground reference points are used to verify the algorithm along with others commonly used. First results show that the average error is between 0,5 and 1m for an Alpine region in Austria which is very close to the error the laser scanner data distributor claims for flat terrain. This study is part of the HIGH-SCAN project (EU IV Framework/Center of Earth Observation), a project whose objective is to provide methods to integrate high satellite imagery and laser scanner data for forest inventory. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings of SPIE SPIE

Adaptive multiresolutional algorithm for high-precision forest floor DTM generation

Proceedings of SPIE, Volume 4035 (1) – Sep 5, 2000

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Publisher
SPIE
Copyright
Copyright © 2003 COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
ISSN
0277-786X
eISSN
1996-756X
DOI
10.1117/12.397782
Publisher site
See Article on Publisher Site

Abstract

This paper focuses on an adaptive multi-resolutional algorithm for generating forest floor digital elevation models by processing the three dimensional data acquired by the laser scanner. The adaptivity of our algorithm ensures that it can be used successfully in flat, hilly, and mountainous terrain and deliver accurate results. A large set of GPS ground reference points are used to verify the algorithm along with others commonly used. First results show that the average error is between 0,5 and 1m for an Alpine region in Austria which is very close to the error the laser scanner data distributor claims for flat terrain. This study is part of the HIGH-SCAN project (EU IV Framework/Center of Earth Observation), a project whose objective is to provide methods to integrate high satellite imagery and laser scanner data for forest inventory.

Journal

Proceedings of SPIESPIE

Published: Sep 5, 2000

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