Статья

Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography

Claude FlenerDepartment of Geography and Geology, University of Turku, FI-20014 Turku, FinlandMatti VaajaDepartment of Real Estate, Planning and Geoinformatics, School of Science and Technology, Aalto University, FI-00076 Espoo, FinlandAnttoni JaakkolaDepartment of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, FinlandAnssi KrooksDepartment of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, FinlandHarri KaartinenDepartment of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, FinlandAntero KukkoDepartment of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, FinlandElina KasviDepartment of Geography and Geology, University of Turku, FI-20014 Turku, FinlandHannu HyyppäDepartment of Real Estate, Planning and Geoinformatics, School of Science and Technology, Aalto University, FI-00076 Espoo, FinlandJuha HyyppäDepartment of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, FinlandPetteri AlhoDepartment of Geography and Geology, University of Turku, FI-20014 Turku, Finland

2013en

ABI

Аннотация

Accurate terrain models are a crucial component of studies of river channel evolution. In this paper we describe a new methodology for creating high-resolution seamless digital terrain models (DTM) of river channels and their floodplains. We combine mobile laser scanning and low-altitude unmanned aerial vehicle (UAV) photography-based methods for creating both a digital bathymetric model of the inundated river channel and a DTM of a point bar of a meandering sub-arctic river. We evaluate mobile laser scanning and UAV-based photogrammetry point clouds against terrestrial laser scanning and combine these data with an optical bathymetric model to create a seamless DTM of two different measurement periods. Using this multi-temporal seamless data, we calculate a DTM of difference that allows a change detection of the meander bend over a one-year period.

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Идентификаторы

DOI: 10.3390/rs5126382

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar