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The Power of Generalized Entropy for Biodiversity Assessment by Remote Sensing: An Open Source Approach

  • Duccio Rocchini
  • Luca Delucchi
  • Giovanni Bacaro
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 227)

Abstract

The assessment of species diversity in relatively large areas has always been a challenging task for ecologists, mainly because of the intrinsic difficulty to judge the completeness of species lists and to undertake sufficient and appropriate sampling. Since the variability of remotely sensed signal is expected to be related to landscape diversity, it could be used as a good proxy of diversity at species level. It has been demonstrated that the relation between species and landscape diversity measured from remotely sensed data or land use maps varies with scale. While traditional metrics supply point descriptions of diversity, generalized entropy’s framework offers a continuum of possible diversity measures, which differ in their sensitivity to rare and abundant reflectance values. In this paper, we aim at: (i) discussing the ecological background beyond the importance of measuring diversity based on generalized entropy and (ii) providing a test on an Open Source tool with its source code for calculating it. We expect that the subject of this paper will stimulate discussions on the opportunities offered by Free and Open Source Software to calculate landscape diversity indices.

Keywords

Biodiversity Generalized entropy Rényi entropy Remote sensing 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Duccio Rocchini
    • 1
    • 2
    • 3
  • Luca Delucchi
    • 3
  • Giovanni Bacaro
    • 4
  1. 1.Center Agriculture Food Environment (C3A), University of TrentoS. Michele all’AdigeItaly
  2. 2.Centre for Integrative Biology, University of TrentoPovoItaly
  3. 3.Fondazione Edmund Mach, Department of Biodiversity and Molecular EcologyResearch and Innovation CentreS. Michele all’AdigeItaly
  4. 4.Department of Life SciencesUniversity of TriesteTriesteItaly

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