Automated Generation of Digital Terrain Model using Point Clouds of Digital Surface Model in Forest Area

Remote Sensing

Kande R.M.U. Bandara¹  Lal Samarakoon²  Rajendra P. Shrestha² 

[1] Faculty of Geomatics, Sabaragamuwa University of Sri Lanka, P.O. Box 2, Belihuloya 70140, Sri Lanka;Asian Institute of Technology, P.O. Box 4, Klong Laung, Pathumthani 12120, Thailand; E-Mails:

关键词: digital elevation model;    digital surface model;    artificial neural networks;   

DOI  :  10.3390/rs3050845

来源: mdpi

【 摘 要 】

At present, most of the digital data acquisition methods generate Digital Surface Model (DSM) and not a Digital Elevation Model (DEM). Conversion from DSM to DEM still has some drawbacks, especially the removing of off terrain point clouds and subsequently the generation of DEM within these spaces even though the methods are automated. In this paper it was intended to overcome this issue by attempting to project off terrain point clouds to the terrain in forest areas using Artificial Neural Networks (ANN) instead of removing them and then filling gaps by interpolation. Five sites were tested and accuracies assessed. They all give almost the same results. In conclusion, the ANN has ability to obtain the DEM by projecting the DSM point clouds and greater accuracies of DEMs were obtained. If the size of the hollow areas resulting from the removal of DSM point clouds are larger the accuracies are reduced.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.