Volume XL-5/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 245-253, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W4-245-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 245-253, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W4-245-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  18 Feb 2015

18 Feb 2015

ACCURACY EVALUATION OF A MOBILE MAPPING SYSTEM WITH ADVANCED STATISTICAL METHODS

I. Toschi1, P. Rodríguez-Gonzálvez2, F. Remondino1, S. Minto1, S. Orlandini3, and A. Fuller4 I. Toschi et al.
  • 13D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
  • 2Dept. of Cartographic and Land Engineering, High School of Ávila, University of Salamanca, Ávila, Spain
  • 3Microgeo, Firenze, Italy
  • 4RIEGL, Vienna, Austria

Keywords: Mobile, Accuracy, Precision, Statistic, Terrestrial, Photogrammetry, Laser scanning

Abstract. This paper discusses a methodology to evaluate the precision and the accuracy of a commercial Mobile Mapping System (MMS) with advanced statistical methods. So far, the metric potentialities of this emerging mapping technology have been studied in few papers, where generally the assumption that errors follow a normal distribution is made. In fact, this hypothesis should be carefully verified in advance, in order to test how well the Gaussian classic statistics can adapt to datasets that are usually affected by asymmetrical gross errors. The workflow adopted in this study relies on a Gaussian assessment, followed by an outlier filtering process. Finally, non-parametric statistical models are applied, in order to achieve a robust estimation of the error dispersion. Among the different MMSs available on the market, the latest solution provided by RIEGL is here tested, i.e. the VMX-450 Mobile Laser Scanning System. The test-area is the historic city centre of Trento (Italy), selected in order to assess the system performance in dealing with a challenging and historic urban scenario. Reference measures are derived from photogrammetric and Terrestrial Laser Scanning (TLS) surveys. All datasets show a large lack of symmetry that leads to the conclusion that the standard normal parameters are not adequate to assess this type of data. The use of non-normal statistics gives thus a more appropriate description of the data and yields results that meet the quoted a-priori errors.