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Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data.

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Title: Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data.
Authors: Monegaglia, Federico1,2 federico.monegaglia@unitn.it, Zolezzi, Guido1, Güneralp, Inci3,4, Henshaw, Alexander J.2, Tubino, Marco1
Source: Environmental Modelling & Software. Jul2018, Vol. 105, p171-186. 16p.
Subject Terms: Meandering rivers, Remote sensing in environmental monitoring, Remote-sensing images, Landsat satellites, Environmental monitoring software
Abstract: We introduce P y RIS, an automated, process-based software for extracting extensive meandering and anabranching river morphodynamics from multitemporal satellite imagery, including a unique ability to quantify river bars dynamics. P y RIS provides three main computations: (i) detection of planform centerline including complex river patterns, (ii) computation of migration vectors between subsequent centerlines, and (iii) analysis of sediment bars dynamics. P y RIS was validated against several test cases in the Amazon River basin, specifically i) main channel extraction from the anabranching Amazon river, ii) migration analysis following a large cutoff on the Ucayali River and iii) detection of sediment bar migration on the Xingu River. Tests prove the capability of P y RIS to detect the main channel in anabranching structures and chute cutoffs. P y RIS can extract extensive morphodynamic information with unprecedented automation levels and reasonable computational effort (5 h for 28 Landsat images of a 240 km reach of the Xingu River on a 3.20 GHz Intel). [ABSTRACT FROM AUTHOR]
Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data.
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  Data: <searchLink fieldCode="DE" term="%22Meandering+rivers%22">Meandering rivers</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing+in+environmental+monitoring%22">Remote sensing in environmental monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Remote-sensing+images%22">Remote-sensing images</searchLink><br /><searchLink fieldCode="DE" term="%22Landsat+satellites%22">Landsat satellites</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+monitoring+software%22">Environmental monitoring software</searchLink>
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  Label: Abstract
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  Data: We introduce P y RIS, an automated, process-based software for extracting extensive meandering and anabranching river morphodynamics from multitemporal satellite imagery, including a unique ability to quantify river bars dynamics. P y RIS provides three main computations: (i) detection of planform centerline including complex river patterns, (ii) computation of migration vectors between subsequent centerlines, and (iii) analysis of sediment bars dynamics. P y RIS was validated against several test cases in the Amazon River basin, specifically i) main channel extraction from the anabranching Amazon river, ii) migration analysis following a large cutoff on the Ucayali River and iii) detection of sediment bar migration on the Xingu River. Tests prove the capability of P y RIS to detect the main channel in anabranching structures and chute cutoffs. P y RIS can extract extensive morphodynamic information with unprecedented automation levels and reasonable computational effort (5 h for 28 Landsat images of a 240 km reach of the Xingu River on a 3.20 GHz Intel). [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.envsoft.2018.03.028
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        Text: English
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      – SubjectFull: Remote-sensing images
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              Text: Jul2018
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