Volume XXXVIII-5/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-5/W12, 319-324, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-5-W12-319-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-5/W12, 319-324, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-5-W12-319-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

  05 Sep 2012

05 Sep 2012

FUSION OF MOBILE LASER SCANNING AND PANORAMIC IMAGES FOR STUDYING RIVER ENVIRONMENT TOPOGRAPHY AND CHANGES

M. Vaaja1, M. Kurkela1, H. Hyyppä1, P. Alho2,1, J. Hyyppä3, A. Kukko3, H. Kaartinen3, E. Kasvi2, S. Kaasalainen3, and P. Rönnholm1 M. Vaaja et al.
  • 1School of Science and Technology, Aalto University, FI-00076 Aalto, Finland
  • 2Department of Geography and Geology, University of Turku, FI-20014 Turku, Finland
  • 3Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, FI-02431 Masala, Finland

Keywords: mobile laser scanning, change detection, digital terrain model, panoramic images, visualisation, fluvial modelling

Abstract. In recent years, laser scanning measurements have been widely used to detect topographic and urban features. In this article, we present a method to integrate mobile laser scanning (MLS) data and panoramic images for producing a textured surface model within a fluvial environment. We also describe the use of the textured surface model to characterize and interpret changes caused by high discharges. The accuracy of MLS-based digital terrain models (DTM) and change detection is evaluated by using static terrestrial laser scanning (TLS) measurements as a reference. The laser scanning data was measured with the mobile mapping system developed in co-operation with the Finnish Geodetic Institute and Aalto University. The boat-based system (BoMMS) has been specially developed for fluvial geomorphology and river mapping. We created panoramic image mosaics by combining sequences of digital images. These methods are suitable for collecting detailed data when traditional methods are unable to gather the data needed for fluvial modelling. The paper also presents a process chain for combining these data sources.