Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

Remote Sensing

Almasi S. Maguya¹  Virpi Junttila² 

[1]Lappeenranta University of Technology, P.O. Box 20, Lappeenranta FI-53851, Finland

关键词: DTM extraction;    airborne LiDAR;    biomass estimation;    tree height estimation;   

DOI  :  10.3390/rs6076524

来源: mdpi

【 摘 要 】

Extracting digital elevation models (DTMs) from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland