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Remote Sensing as a Tool for Analysing Channel Dynamics and Geomorphic Effects of Floods

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Book cover Flood Monitoring through Remote Sensing

Part of the book series: Springer Remote Sensing/Photogrammetry ((SPRINGERREMO))

Abstract

Over the past two decades, the use of optical remote sensing in fluvial geomorphology has become widely employed for several applications, due to improvements in geospatial technologies and data availability. However, applications focused on change detection of channel dynamics and geomorphic response to individual flood events are still relatively rare. Insights into the complexity of interactions driving geomorphic changes might be obtained by application of diverse remote sensing approaches, depending on several factors (e.g. temporal and spatial resolution, magnitude of detected change). An overview about remote sensing as a tool for channel dynamics and geomorphic response to flood detection is illustrated, including discussion about advantages and limitations of optical remote sensing.

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Acknowledgements

Fondazione Cariparo is gratefully acknowledged for funding M. Righini PhD fellowship. We thank the anonymous reviewers and the book editors for their comments and helpful suggestions.

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  1. Department of Geosciences, University of Padova, Padova, Italy

    Margherita Righini & Nicola Surian

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  1. Margherita Righini
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Correspondence to Margherita Righini .

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  1. Istituto di Studi sui Sistemi, Intelligenti per l’Automazione (ISSIA), Consiglio Nazionale delle Ricerche (CNR), Bari, Italy

    Alberto Refice

  2. Istituto di Studi sui Sistemi, Intelligenti per l’Automazione (ISSIA), Consiglio Nazionale delle Ricerche (CNR), Bari, Italy

    Annarita D'Addabbo

  3. Department of Earth and Environmental Sciences, University of Bari, Bari, Italy

    Domenico Capolongo

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Righini, M., Surian, N. (2018). Remote Sensing as a Tool for Analysing Channel Dynamics and Geomorphic Effects of Floods. In: Refice, A., D'Addabbo, A., Capolongo, D. (eds) Flood Monitoring through Remote Sensing. Springer Remote Sensing/Photogrammetry. Springer, Cham. https://doi.org/10.1007/978-3-319-63959-8_2

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