Optical sensing for stream flow observations: a review

Images are revolutionizing the way we sense and characterize the environment by offering higher spatial and temporal coverage in ungauged environments at competitive costs. In this review, we illustrate the major image-based approaches that have been lately adopted within the hydrological research c...

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Main Authors: Flavia Tauro, Andrea Petroselli, Salvatore Grimaldi
Format: Article
Language:English
Published: PAGEPress Publications 2018-04-01
Series:Journal of Agricultural Engineering
Subjects:
Online Access:https://www.agroengineering.org/index.php/jae/article/view/836
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spelling doaj-5323346bfa0a4b75ac18b41baa68ddff2020-11-25T03:56:16ZengPAGEPress PublicationsJournal of Agricultural Engineering1974-70712239-62682018-04-014910.4081/jae.2018.836Optical sensing for stream flow observations: a reviewFlavia Tauro0Andrea Petroselli1Salvatore Grimaldi2Centro per l’Innovazione Tecnologica e lo Sviluppo del Territorio, University of Tuscia, ViterboDepartment of Economics, Engineering, Society and Business Organization, University of Tuscia, ViterboDepartment for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, Viterbo, Italy; Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NYImages are revolutionizing the way we sense and characterize the environment by offering higher spatial and temporal coverage in ungauged environments at competitive costs. In this review, we illustrate the major image-based approaches that have been lately adopted within the hydrological research community. Although many among such methodologies have been developed some decades ago, recent efforts have been devoted to their transition from laboratories to operational outdoor settings. Sample applications of image-based techniques include flow discharge estimation in riverine environments, clogging dynamics in irrigation systems, and flow diagnostics in engineering infrastructures. The potential of such image-based approaches towards fully remote observations is also illustrated through a simple experiment with an unmanned aerial vehicle.https://www.agroengineering.org/index.php/jae/article/view/836Ungauged catchmentsexperimental monitoringimagesoptical sensinglarge scaleparticle image velocimetryparticle tracking velocimetry.
collection DOAJ
language English
format Article
sources DOAJ
author Flavia Tauro
Andrea Petroselli
Salvatore Grimaldi
spellingShingle Flavia Tauro
Andrea Petroselli
Salvatore Grimaldi
Optical sensing for stream flow observations: a review
Journal of Agricultural Engineering
Ungauged catchments
experimental monitoring
images
optical sensing
large scaleparticle image velocimetry
particle tracking velocimetry.
author_facet Flavia Tauro
Andrea Petroselli
Salvatore Grimaldi
author_sort Flavia Tauro
title Optical sensing for stream flow observations: a review
title_short Optical sensing for stream flow observations: a review
title_full Optical sensing for stream flow observations: a review
title_fullStr Optical sensing for stream flow observations: a review
title_full_unstemmed Optical sensing for stream flow observations: a review
title_sort optical sensing for stream flow observations: a review
publisher PAGEPress Publications
series Journal of Agricultural Engineering
issn 1974-7071
2239-6268
publishDate 2018-04-01
description Images are revolutionizing the way we sense and characterize the environment by offering higher spatial and temporal coverage in ungauged environments at competitive costs. In this review, we illustrate the major image-based approaches that have been lately adopted within the hydrological research community. Although many among such methodologies have been developed some decades ago, recent efforts have been devoted to their transition from laboratories to operational outdoor settings. Sample applications of image-based techniques include flow discharge estimation in riverine environments, clogging dynamics in irrigation systems, and flow diagnostics in engineering infrastructures. The potential of such image-based approaches towards fully remote observations is also illustrated through a simple experiment with an unmanned aerial vehicle.
topic Ungauged catchments
experimental monitoring
images
optical sensing
large scaleparticle image velocimetry
particle tracking velocimetry.
url https://www.agroengineering.org/index.php/jae/article/view/836
work_keys_str_mv AT flaviatauro opticalsensingforstreamflowobservationsareview
AT andreapetroselli opticalsensingforstreamflowobservationsareview
AT salvatoregrimaldi opticalsensingforstreamflowobservationsareview
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