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

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: Springer Science and Business Media LLC
• 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