Abstract
The main aim of the work presented here has been to evaluate which combination of filtering and interpolation algorithms can offer the best DTM accuracy in conditions involving very dense forest in mountainous areas. The study area was in the Sudety Mountains of southwestern Poland, close to the Czech border. For each filtration, almost 100 DTMs were generated, with final analysis confined to just 6 most-accurate models. The results show that slope and particularly undergrowth vegetation are the most important factors influencing DTM accuracy in dense mountain forests. However, all methods of interpolation are capable of reaching very similar levels of error after proper calibration.
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