The knowledge of the hydro-morphological evolution of lowland rivers is essential to develop integrated river management plans. Satellite data can provide continuous and efficient means to monitor fluvial geomorphological changes at various spatiotemporal scales. In this study, an automatic classification method was exploited to analyze the evolution of a 40 km reach of the Italian Po River from 1986 to 2020. Public domain multispectral satellite data acquired by Landsat 4-5-TM, Landsat-8-OLI and Sentinel-2-MSI were processed to extract the wet-channel and its variations over time. Very high-resolution GeoEye-01 and WorldView-02 images were employed for validating the classification method. The overall accuracy, obtained by multitemporal controls with very high-resolution images, was always greater than 0.90 for all the missions, showing that the classification accuracy remains consistent through time. Combining satellite data with hydrological measurements permitted to monitor the river at the reach scale and investigate the effects of river restoration works.

Monitoring the morphological evolution of a reach of the Italian Po River using multispectral satellite imagery and stage data

Cavallo C.;Papa M. N.;
2021-01-01

Abstract

The knowledge of the hydro-morphological evolution of lowland rivers is essential to develop integrated river management plans. Satellite data can provide continuous and efficient means to monitor fluvial geomorphological changes at various spatiotemporal scales. In this study, an automatic classification method was exploited to analyze the evolution of a 40 km reach of the Italian Po River from 1986 to 2020. Public domain multispectral satellite data acquired by Landsat 4-5-TM, Landsat-8-OLI and Sentinel-2-MSI were processed to extract the wet-channel and its variations over time. Very high-resolution GeoEye-01 and WorldView-02 images were employed for validating the classification method. The overall accuracy, obtained by multitemporal controls with very high-resolution images, was always greater than 0.90 for all the missions, showing that the classification accuracy remains consistent through time. Combining satellite data with hydrological measurements permitted to monitor the river at the reach scale and investigate the effects of river restoration works.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4778762
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