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International Conference on Computational Science and Its Applications

ICCSA 2017: Computational Science and Its Applications – ICCSA 2017 pp 600–612Cite as

A GIS-Based Model for the Analysis of Ecological Connectivity

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

Abstract

A model for the calculation of Potential Ecological Network at regional level has been presented in this paper. Through the use of GIS techniques and Natural Protected Areas and Land Use Map GIS datasets, the proposed model links two Ecological Network approaches (Species-Specific and Land Units) using the Least - Cost Path (LCP) algorithm. The nodes of the Ecological Potential Network have been analyzed using the Graph Theory. Specific GIS workflows have been set up to model the ecological connectivity in problematic mapping conditions, such as under road bridges and on the riverbanks. The main workflow requires a rasterization of the input datasets to allow the LCP algorithm application. The variations of the pixel resolution have been analyzed in terms of accuracy of the output and computation time of the model. The results underline an emerging property of Potential Ecological Networks, the Secondary Nodes, which are a set of nodes at the intersection of Linkages built by the LCP algorithm.

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Author information

Authors and Affiliations

  1. Department of Astronautical, Electrical and Energy Engineering (DIAEE), Sapienza, University of Rome, Via Eudossiana 18, 00184, Rome, Italy

    Andrea Fiduccia, Francesca Pagliaro & Luca Gugliermetti

  2. Department of Design and Planning in Complex Environments, IUAV University, Santa Croce 1957, Ca’ Tron, 30135, Venice, Italy

    Leonardo Filesi

Authors
  1. Andrea Fiduccia
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  2. Francesca Pagliaro
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  3. Luca Gugliermetti
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  4. Leonardo Filesi
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Corresponding author

Correspondence to Andrea Fiduccia .

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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Fiduccia, A., Pagliaro, F., Gugliermetti, L., Filesi, L. (2017). A GIS-Based Model for the Analysis of Ecological Connectivity. 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_43

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  • DOI: https://doi.org/10.1007/978-3-319-62401-3_43

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62400-6

  • Online ISBN: 978-3-319-62401-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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