Open AccessCOMPARISON OF DIGITAL SURFACE MODELS FOR SNOW DEPTH MAPPING WITH UAV AND AERIAL CAMERAS
Author(s) -
R. Boesch,
Yves Bühler,
M. Marty,
Christian Ginzler
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b8-453-2016
Subject(s) - photogrammetry , software , point cloud , computer vision , artificial intelligence , computer science , remote sensing , gnss applications , snow , digital camera , computer graphics (images) , digital surface , workflow , global positioning system , geography , lidar , meteorology , telecommunications , database , programming language
Photogrammetric workflows for aerial images have improved over the last years in a typically black-box fashion. Most parameters for building dense point cloud are either excessive or not explained and often the progress between software releases is poorly documented. On the other hand, development of better camera sensors and positional accuracy of image acquisition is significant by comparing product specifications. This study shows, that hardware evolutions over the last years have a much stronger impact on height measurements than photogrammetric software releases. <br><br> Snow height measurements with airborne sensors like the ADS100 and UAV-based DSLR cameras can achieve accuracies close to GSD * 2 in comparison with ground-based GNSS reference measurements. Using a custom notch filter on the UAV camera sensor during image acquisition does not yield better height accuracies. UAV based digital surface models are very robust. Different workflow parameter variations for ADS100 and UAV camera workflows seem to have only random effects.