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  1. Pubblicazioni

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

Articolo
Data di Pubblicazione:
2022
Citazione:
Double down on remote sensing for biodiversity estimation: a biological mindset / Rocchini, D; Torresani, M; Beierkuhnlein, C; Feoli, E; Foody, Gm; Lenoir, J; Malavasi, M; Moudry, V; Simova, P; Ricotta, C. - In: COMMUNITY ECOLOGY. - ISSN 1585-8553. - 23:3(2022), pp. 267-276. [10.1007/s42974-022-00113-7]
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.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Beta-diversity; Biodiversity; Earth observation; Ecological informatics; Grain; Plant optical types; Remote sensing; Satellite imagery
Elenco autori:
Rocchini, D; Torresani, M; Beierkuhnlein, C; Feoli, E; Foody, Gm; Lenoir, J; Malavasi, M; Moudry, V; Simova, P; Ricotta, C
Autori di Ateneo:
MALAVASI Marco
Link alla scheda completa:
https://iris.uniss.it/handle/11388/313809
Pubblicato in:
COMMUNITY ECOLOGY
Journal
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