A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography
Tekijät: Claude Flener, Matti Vaaja, Anttoni Jaakkola, Anssi Krooks, Harri Kaartinen, Antero Kukko, Elina Kasvi, Hannu Hyyppä, Juha Hyyppä, Petteri Alho
Kustantaja: MDPI
Julkaisuvuosi: 2013
Journal: Remote Sensing
Lehden akronyymi: Remote Sens
Numero sarjassa: 12
Vuosikerta: 5
Numero: 12
Aloitussivu: 6382
Lopetussivu: 6407
Sivujen määrä: 26
ISSN: 2072-4292
DOI: https://doi.org/10.3390/rs5126382
Tiivistelmä
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.
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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