Cargando…

Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization

The 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Rivas Casado, Mónica, González, Rocío Ballesteros, Ortega, José Fernando, Leinster, Paul, Wright, Ros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676608/
https://www.ncbi.nlm.nih.gov/pubmed/28954434
http://dx.doi.org/10.3390/s17102210
_version_ 1783277086611341312
author Rivas Casado, Mónica
González, Rocío Ballesteros
Ortega, José Fernando
Leinster, Paul
Wright, Ros
author_facet Rivas Casado, Mónica
González, Rocío Ballesteros
Ortega, José Fernando
Leinster, Paul
Wright, Ros
author_sort Rivas Casado, Mónica
collection PubMed
description The 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.
format Online
Article
Text
id pubmed-5676608
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-56766082017-11-17 Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization Rivas Casado, Mónica González, Rocío Ballesteros Ortega, José Fernando Leinster, Paul Wright, Ros Sensors (Basel) Article The 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. MDPI 2017-09-26 /pmc/articles/PMC5676608/ /pubmed/28954434 http://dx.doi.org/10.3390/s17102210 Text en © 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/).
spellingShingle Article
Rivas Casado, Mónica
González, Rocío Ballesteros
Ortega, José Fernando
Leinster, Paul
Wright, Ros
Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title_full Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title_fullStr Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title_full_unstemmed Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title_short Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization
title_sort towards a transferable uav-based framework for river hydromorphological characterization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676608/
https://www.ncbi.nlm.nih.gov/pubmed/28954434
http://dx.doi.org/10.3390/s17102210
work_keys_str_mv AT rivascasadomonica towardsatransferableuavbasedframeworkforriverhydromorphologicalcharacterization
AT gonzalezrocioballesteros towardsatransferableuavbasedframeworkforriverhydromorphologicalcharacterization
AT ortegajosefernando towardsatransferableuavbasedframeworkforriverhydromorphologicalcharacterization
AT leinsterpaul towardsatransferableuavbasedframeworkforriverhydromorphologicalcharacterization
AT wrightros towardsatransferableuavbasedframeworkforriverhydromorphologicalcharacterization