Towards a transferable UAV-based framework for river hydromorphological characterization

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dc.contributor.authorRivas Casado, Monica
dc.contributor.authorBallesteros Gonzalez, Rocio
dc.contributor.authorFernando Ortega, Jose
dc.contributor.authorLeinster, Paul
dc.contributor.authorWright, Ros
dc.date.accessioned2017-09-28T17:33:20Z
dc.date.available2017-09-28T17:33:20Z
dc.date.issued2017-09-26
dc.description.abstractThe multiple protocols that have been developed to characterize river hydromorphology, partly in response to legislative drivers such as the European Union Water Framework Directive (EU WFD), make the comparison of results obtained in different countries challenging. Recent studies have analyzed the comparability of existing methods, with remote sensing based approaches being proposed as a potential means of harmonizing hydromorphological characterization protocols. However, the resolution achieved by remote sensing products may not be sufficient to assess some of the key hydromorphological features that are required to allow an accurate characterization. Methodologies based on high resolution aerial photography taken from Unmanned Aerial Vehicles (UAVs) have been proposed by several authors as potential approaches to overcome these limitations. Here, we explore the applicability of an existing UAV based framework for hydromorphological characterization to three different fluvial settings representing some of the distinct ecoregions defined by the WFD geographical intercalibration groups (GIGs). The framework is based on the automated recognition of hydromorphological features via tested and validated Artificial Neural Networks (ANNs). Results show that the framework is transferable to the Central-Baltic and Mediterranean GIGs with accuracies in feature identification above 70%. Accuracies of 50% are achieved when the framework is implemented in the Very Large Rivers GIG. The framework successfully identified vegetation, deep water, shallow water, riffles, side bars and shadows for the majority of the reaches. However, further algorithm development is required to ensure a wider range of features (e.g., chutes, structures and erosion) are accurately identified. This study also highlights the need to develop an objective and fit for purpose hydromorphological characterization framework to be adopted within all EU member states to facilitate comparison of results.en_UK
dc.identifier.citationRivas Casado, Ballesteros R, Ortega JF, et al., (2017) Towards a transferable UAV-based framework for river hydromorphological characterization. Sensors, Volume 17, Issue 10, 2017, article number 2210en_UK
dc.identifier.cris18531277
dc.identifier.issn1424-8220
dc.identifier.urihttp://dx.doi.org/10.3390/s17102210
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/12560
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rights© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.subjecthydromorphologyen_UK
dc.subjectintercalibrationen_UK
dc.subjectunmanned aerial vehicleen_UK
dc.subjectphotogrammetryen_UK
dc.subjectartificial neural networken_UK
dc.subjectwater framework directiveen_UK
dc.titleTowards a transferable UAV-based framework for river hydromorphological characterizationen_UK
dc.typeArticleen_UK

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