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The Use of Geomorphological Descriptors and Landsat-8 Spectral Indices Data for Flood Areas Evaluation: A Case Study of Lato River Basin

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Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10407))

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Abstract

In the last few years, the scientific community has dedicated a strong effort for the rapid identification and mapping of flood risk. Last generation models have often taken advantage (even without of in-situ measurements) of the distributed information provided from remotely sensed data. In this work is proposed a multidisciplinary approach to reproduce maps of flooded areas. The method compared spectral descriptors to estimate the areas at risk of flooding in the Lato river basin (Puglia region - Southern Italy) using the ground effects caused by flood events. The inundated areas, obtained with a 2D hydraulic model, were used as reference for Landsat-8 spectral indices. The selection of the most appropriate spectral index was achieved using the binary classifiers test. Lastly, the adopted procedure provided also the calibration of different geomorphological descriptors for a rapid identification of areas at risk of flooding by using Digital Elevation Models.

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Author information

Authors and Affiliations

  1. Politecnico di Bari, via Orabona 4, 70125, Bari, Italy

    Vincenzo Totaro, Andrea Gioia, Antonio Novelli & Grazia Caradonna

Authors
  1. Vincenzo Totaro
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  2. Andrea Gioia
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  3. Antonio Novelli
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  4. Grazia Caradonna
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Corresponding author

Correspondence to Andrea Gioia .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Trieste, Trieste, Italy

    Giuseppe Borruso

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  9. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  10. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

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Totaro, V., Gioia, A., Novelli, A., Caradonna, G. (2017). The Use of Geomorphological Descriptors and Landsat-8 Spectral Indices Data for Flood Areas Evaluation: A Case Study of Lato River Basin. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10407. Springer, Cham. https://doi.org/10.1007/978-3-319-62401-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-62401-3_3

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