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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]
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Database: GreenFILE
Description
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]
ISSN:13648152
DOI:10.1016/j.envsoft.2018.03.028