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Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study

Rocchini, Duccio and Bacaro, Giovanni and Chirici, Gherardo and Da Re, Daniele and Feilhauer, Hannes and Foody, Giles M. and Galluzzi, Marta and Garzon-Lopez, Carol X. and Gillespie, Thomas W. and He, Kate S. and Lenoir, Jonathan and Marcantonio, Matteo and Nagendra, Harini and Ricotta, Carlo and Rommel, Edvinas and Schmidtlein, Sebastian and Skidmore, Andrew and Van de Kerchove, Ruben and Wegmann, Martin and Rugani, Benedetto (2018) Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study. Ecological Indicators, 85, pp. 983-990. Elsevier. doi: 10.1016/j.ecolind.2017.09.055. ISSN 1470-160X.

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Official URL: http://www.sciencedirect.com/science/article/pii/S1470160X17306234

Abstract

Assessing biodiversity from field-based data is difficult for a number of practical reasons: (i) establishing the total number of sampling units to be investigated and the sampling design (e.g. systematic, random, stratified) can be difficult; (ii) the choice of the sampling design can affect the results; and (iii) defining the focal population of interest can be challenging. Satellite remote sensing is one of the most cost-effective and comprehensive approaches to identify biodiversity hotspots and predict changes in species composition. This is because, in contrast to field-based methods, it allows for complete spatial coverages of the Earth's surface under study over a short period of time. Furthermore, satellite remote sensing provides repeated measures, thus making it possible to study temporal changes in biodiversity. While taxonomic diversity measures have long been established, problems arising from abundance related measures have not been yet disentangled. Moreover, little has been done to account for functional diversity besides taxonomic diversity measures. The aim of this manuscript is to propose robust measures of remotely sensed heterogeneity to perform exploratory analysis for the detection of hotspots of taxonomic and functional diversity of plant species.

Item URL in elib:https://elib.dlr.de/116988/
Document Type:Article
Title:Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Rocchini, DuccioResearch and Innovation Centre, San Michele all'Adige, Trentino, ItalyUNSPECIFIEDUNSPECIFIED
Bacaro, GiovanniUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Chirici, GherardoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Da Re, DanieleUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Feilhauer, HannesUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Foody, Giles M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Galluzzi, MartaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Garzon-Lopez, Carol X.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Gillespie, Thomas W.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
He, Kate S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lenoir, JonathanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Marcantonio, MatteoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Nagendra, HariniUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ricotta, CarloUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Rommel, EdvinasUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schmidtlein, SebastianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Skidmore, AndrewUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Van de Kerchove, RubenUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wegmann, MartinUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Rugani, BenedettoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:February 2018
Journal or Publication Title:Ecological Indicators
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:85
DOI:10.1016/j.ecolind.2017.09.055
Page Range:pp. 983-990
Publisher:Elsevier
ISSN:1470-160X
Status:Published
Keywords:Cartograms; Functional diversity; Remote sensing; Rao's quadratic diversity; Satellite imagery; Spectral rarefaction; Taxonomic diversity
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:11 Dec 2017 13:21
Last Modified:19 Nov 2021 20:21

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