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

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.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
07 Faculty of Science > Department of Astrophysics
Dewey Decimal Classification:530 Physics
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Ecological Modeling
Uncontrolled Keywords:Ecological Modeling, Ecology, Evolution, Behavior and Systematics Biodiversity, Ecological informatics, Modelling, Remote sensing, Satellite imagery
Language:English
Date:1 December 2022
Deposited On:16 Apr 2023 15:50
Last Modified:25 Dec 2024 04:33
Publisher:Elsevier
ISSN:1476-945X
Additional Information:Acknowledgements: This study has received funding from the project SHOWCASE (SHOW- CASingsynergies between agriculture, biodiversity and ecosystems ser- vices tohelp farmers capitalising on native biodiversity) within the EuropeanUnion’s Horizon 2020 Researcher and Innovation Programme under grantagreement No. 862480. DR was also supported by the Horizon Europe project Earthbridge. PZ was supported by LifeWatch Italy through the project LifeWatchPLUS (CIR01_00028). RF is supported by the Swiss National Science Foundation, Switzerland SNSF175529. ETo is supported by the Estonian Research Council, grant code MOBJD1030. MM is supported by the FRS-FNRS and by the “Action de Recherche concertée” grant number 17/22-086. DR, MM, MG and ETh contributed to the development of the R function and to the analysis. DR, PZ and ETh contributed to the implementation of the figures. All the authors contributed to the writing of the manuscript. The rasterdiv package that contains the new function proposed can be downloaded at https://github.com/mattmar/rasterdiv or directly from the CRAN (https://CRAN.R-project.org/package=rasterdiv). The hyperspectral images of Santa Barbara of June 2009 and 2011 can be respectively retrieved from https://popo.jpl.nasa.gov/avcl/y09_data/f090826t01p00r08.tar.gz and https://popo.jpl.nasa.gov/avcl/y11_data/f110719t01p00r19.tar.gz. The images of Kangaroo Island can be retrieved from https://scihub.copernicus.eu/dhus/#/home. Data availability: The code and the data used are opensource and available online.
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.ecocom.2023.101029
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