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  1. Pubblicazioni

Integrals of life: Tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao's Q index

Articolo
Data di Pubblicazione:
2023
Citazione:
Integrals of life: Tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao's Q index / Thouverai, E.; Marcantonio, M.; Lenoir, J.; Galfre, M.; Marchetto, E.; Bacaro, G.; Cazzolla Gatti, R.; Da Re, D.; Di Musciano, M.; Furrer, R.; Malavasi, M.; Moudry, V.; Nowosad, J.; Pedrotti, F.; Pelorosso, R.; Pezzi, G.; Simova, P.; Ricotta, C.; Silvestri, S.; Tordoni, E.; Torresani, M.; Vacchiano, G.; Zannini, P.; Rocchini, D.. - In: ECOLOGICAL COMPLEXITY. - ISSN 1476-945X. - 52:(2023), p. 101029. [10.1016/j.ecocom.2023.101029]
Abstract:
Spatio-ecological heterogeneity is strongly linked to many ecological processes and functions such as plant species diversity patterns and change, metapopulation dynamics, and gene flow. Remote sensing is particularly useful for measuring spatial heterogeneity of ecosystems over wide regions with repeated measurements in space and time. Besides, developing free and open source algorithms for ecological modelling from space is vital to allow to prove workflows of analysis reproducible. From this point of view, NASA developed programs like the Surface Biology and Geology (SBG) to support the development of algorithms for exploiting spaceborne remotely sensed data to provide a relatively fast but accurate estimate of ecological properties in vast areas over time. Most of the indices to measure heterogeneity from space are point descriptors : they catch only part of the whole heterogeneity spectrum. Under the SBG umbrella, in this paper we provide a new R function part of the rasterdiv R package which allows to calculate spatio-ecological heterogeneity and its variation over time by considering all its possible facets. The new function was tested on two different case studies, on multi- and hyperspectral images, proving to be an effective tool to measure heterogeneity and detect its changes over time.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Thouverai, E.; Marcantonio, M.; Lenoir, J.; Galfre, M.; Marchetto, E.; Bacaro, G.; Cazzolla Gatti, R.; Da Re, D.; Di Musciano, M.; Furrer, R.; Malavasi, M.; Moudry, V.; Nowosad, J.; Pedrotti, F.; Pelorosso, R.; Pezzi, G.; Simova, P.; Ricotta, C.; Silvestri, S.; Tordoni, E.; Torresani, M.; Vacchiano, G.; Zannini, P.; Rocchini, D.
Autori di Ateneo:
MALAVASI Marco
Link alla scheda completa:
https://iris.uniss.it/handle/11388/313750
Pubblicato in:
ECOLOGICAL COMPLEXITY
Journal
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