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Double down on remote sensing for biodiversity estimation: a biological mindset

Rocchini, Duccio; Torresani, Michele; Beierkuhnlein, Carl; Feoli, Enrico; Foody, Giles M.; Lenoir, Jonathan; Malavasi, Marco; Moudrý, Vítězslav; Šímová, Petra; Ricotta, Carlo

Authors

Duccio Rocchini

Michele Torresani

Carl Beierkuhnlein

Enrico Feoli

GILES FOODY giles.foody@nottingham.ac.uk
Professor of Geographical Information

Jonathan Lenoir

Marco Malavasi

Vítězslav Moudrý

Petra Šímová

Carlo Ricotta



Abstract

In the light of unprecedented planetary changes in biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential for informing policy and sustainable development. Biodiversity monitoring is a challenge, especially for large areas such as entire continents. Nowadays, spaceborne and airborne sensors provide information that incorporate wavelengths that cannot be seen nor imagined with the human eye. This is also now accomplished at unprecedented spatial resolutions, defined by the pixel size of images, achieving less than a meter for some satellite images and just millimeters for airborne imagery. Thanks to different modeling techniques, it is now possible to study functional diversity changes over different spatial and temporal scales. At the heart of this unifying framework are the “spectral species”—sets of pixels with a similar spectral signal—and their variability over space. The aim of this paper is to summarize the power of remote sensing for directly estimating plant species diversity, particularly focusing on the spectral species concept.

Citation

Rocchini, D., Torresani, M., Beierkuhnlein, C., Feoli, E., Foody, G. M., Lenoir, J., …Ricotta, C. (2022). Double down on remote sensing for biodiversity estimation: a biological mindset. Community Ecology, https://doi.org/10.1007/s42974-022-00113-7

Journal Article Type Article
Acceptance Date Sep 12, 2022
Online Publication Date Oct 11, 2022
Publication Date Oct 11, 2022
Deposit Date Oct 19, 2022
Publicly Available Date Oct 19, 2022
Journal Community Ecology
Print ISSN 1585-8553
Electronic ISSN 1588-2756
Publisher Akadémiai Kiadó
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1007/s42974-022-00113-7
Keywords Ecology; Ecology, Evolution, Behavior and Systematics
Public URL https://nottingham-repository.worktribe.com/output/12616814
Publisher URL https://link.springer.com/article/10.1007/s42974-022-00113-7

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