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Remote Sens. 2016, 8(8), 650; doi:10.3390/rs8080650

Quantifying the Effect of Aerial Imagery Resolution in Automated Hydromorphological River Characterisation

1
School of Energy, Environment and Agrifood, Cranfield University, Cranfield MK430AL, UK
2
Regional Centre of Water Research (UCLM), Ctra. de las Peñas km 3.2, Albacete 02071, Spain
3
National Fisheries Services, Environment Agency, Threshelfords Business Park, Inworth Rd., Feering, Essex CO6 1UD, UK
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Farid Melgani, Francesco Nex, Norman Kerle and Prasad S. Thenkabail
Received: 5 June 2016 / Revised: 23 July 2016 / Accepted: 3 August 2016 / Published: 10 August 2016
(This article belongs to the Special Issue Recent Trends in UAV Remote Sensing)
View Full-Text   |   Download PDF [7397 KB, uploaded 10 August 2016]   |  

Abstract

Existing regulatory frameworks aiming to improve the quality of rivers place hydromorphology as a key factor in the assessment of hydrology, morphology and river continuity. The majority of available methods for hydromorphological characterisation rely on the identification of homogeneous areas (i.e., features) of flow, vegetation and substrate. For that purpose, aerial imagery is used to identify existing features through either visual observation or automated classification techniques. There is evidence to believe that the success in feature identification relies on the resolution of the imagery used. However, little effort has yet been made to quantify the uncertainty in feature identification associated with the resolution of the aerial imagery. This paper contributes to address this gap in knowledge by contrasting results in automated hydromorphological feature identification from unmanned aerial vehicles (UAV) aerial imagery captured at three resolutions (2.5 cm, 5 cm and 10 cm) along a 1.4 km river reach. The results show that resolution plays a key role in the accuracy and variety of features identified, with larger identification errors observed for riffles and side bars. This in turn has an impact on the ecological characterisation of the river reach. The research shows that UAV technology could be essential for unbiased hydromorphological assessment. View Full-Text
Keywords: unmanned aerial vehicle; photogrammetry; resolution; comparison; hydromorphology; river management unmanned aerial vehicle; photogrammetry; resolution; comparison; hydromorphology; river management
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rivas Casado, M.; Ballesteros Gonzalez, R.; Wright, R.; Bellamy, P. Quantifying the Effect of Aerial Imagery Resolution in Automated Hydromorphological River Characterisation. Remote Sens. 2016, 8, 650.

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