The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-1/W1-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-303-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-303-2023
25 May 2023
 | 25 May 2023

EXPLOITING POLE-LIKE OBJECTS FROM CADASTRES FOR SUB-METRE ACCURATE INTEGRATED GEOREFERENCING OF LOW-COST MOBILE MAPPING SYSTEMS

J. Meyer, S. Nebiker, S. Schürmann, E. Ferrari, and M. Ammann

Keywords: Georeferencing, Mobile Mapping, Urban, Localization, RGB-D, Depth Map, Point cloud, Pole-like objects

Abstract. Accurately georeferenced data acquired using mobile mapping systems is of great importance for many geospatial applications. The accuracy of direct georeferencing – the standard procedure in the field of outdoor mobile mapping – strongly relies on GNSS reception and therefore varies greatly depending on the environment. By incorporating control point observations, integrated georeferencing enables homogenous accuracy and reliability over the whole mapping perimeter. Unfortunately, exact measurement and documentation of control points is needed, which often must be done manually. To automate this process, approaches from the field of autonomous vehicles use pole-like objects to support localization in complex urban environments, with the disadvantage of requiring a prior mapping campaign. However, various classes of pole-like objects have been recorded with accurate location and entered in public cadastres, so they could serve as 2D control points. In this paper, we present an approach for improving the trajectory accuracy in challenging urban environments by means of integrated georeferencing. It uses range image observations to pole-like objects from publicly available cadastres. Our approach achieves sub-metre accuracy, with a maximal cross-track difference of 98 cm, using real-world data acquired with our low-cost mobile mapping system. We further demonstrate that it significantly improves discontinuities and inaccuracy peaks in direct georeferencing and that the limiting factors are errors in the depth estimation of available range imaging sensors.