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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2018-04-01
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Online Access: | https://www.agroengineering.org/index.php/jae/article/view/836 |
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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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