Scholarly record

PHOTOGRAMMETRIC METHODS FOR DIGITAL HEIGHT MODELS

Dragoş Badea

Abstract

Technologies based on photogrammetric and remote sensing sensors represent the usual way for obtaining digital height and position data. This paper is dedicated to LiDAR data filtering for a DEM generation. The main purpose is presentation of a semi-automated method of filtering using mathematical and statistical algorithms for a valid data set. The method involves point cloud data filtering and interpolation. The principle of it is to validate an error free data set and construct the DSM from the last pulse reflexing, using statistical filtering and spatial polynomial interpolation. Those can be easily implemented by programming procedures; therefore modification of the algorithm in order to get the best possible results from a local DEM can be done with ease. Depending of the application requiring the DEM, a semi-automated filtering and interpolation method of LiDAR data may represent the best approach. A general fully automated extraction of DEM from DSM is a suitable approach for large scale applications where small details are usually ignored or considered not important. The method keeps its general availability for all LiDAR data. The approach was tested against a number of local surveying sites and the results conclusions were as expected. The methods of filtering and generation of DEM are continuing the PHD topic which stated at Institute of Photogrammetry and GeoInformation at the University of Hannover (IPI).

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DOI resolver: doi.org/10.5593/sgem2018/2.3/s11.066

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