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Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring

Rocchini, Duccio; Luque, Sandra; Pettorelli, Nathalie; Bastin, Lucy; Doktor, Daniel; Faedi, Nicolo; Feilhauer, Hannes; Feret, Jean-Baptiste; Foody, Giles M.; Gavish, Yoni; Godinho, Sergio; Kunin, William E.; Lausch, Angela; Leitao, Pedro J.; Marcantonio, Matteo; Neteler, Markus; Ricotta, Carlo; Schmidtlein, Sebastian; Vihervaara, Petteri; Wegmann, Martin; Nagendra, Harini


Duccio Rocchini

Sandra Luque

Nathalie Pettorelli

Lucy Bastin

Daniel Doktor

Nicolo Faedi

Hannes Feilhauer

Jean-Baptiste Feret

Professor of Geographical Information

Yoni Gavish

Sergio Godinho

William E. Kunin

Angela Lausch

Pedro J. Leitao

Matteo Marcantonio

Markus Neteler

Carlo Ricotta

Sebastian Schmidtlein

Petteri Vihervaara

Martin Wegmann

Harini Nagendra


Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, overall when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this view, airborne or satellite remote sensing allow to gather information over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (beta-diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure beta-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao's Q diversity. Each of these measures allow to solve one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating beta-diversity from remotely sensed imagery and potentially relate them to species diversity in the field.


Rocchini, D., Luque, S., Pettorelli, N., Bastin, L., Doktor, D., Faedi, N., …Nagendra, H. (in press). Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring. Methods in Ecology and Evolution, ISSN 2041-210X

Journal Article Type Article
Acceptance Date Nov 11, 2017
Deposit Date Jan 17, 2018
Publicly Available Date Aug 7, 2019
Journal Methods in Ecology and Evolution
Electronic ISSN 2041-210X
Publisher Wiley Open Access
Peer Reviewed Peer Reviewed
Keywords Beta-diversity, Kohonen self-organising feature maps, Rao's Q diversity index, remote sensing, satellite imagery, Sparse Generalized Dissimilarity Model, spectral species concept
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Copyright Statement Copyright information regarding this work can be found at the following address:
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MEE-17-09-804_R1.pdf (4.7 Mb)

Copyright Statement
Copyright information regarding this work can be found at the following address:

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