Measuring biodiversity is a key issue in ecology to guarantee effective indicators of ecosystem health at different spatial and time scales. However, estimating biodiversity from field observations might present difficulties related to costs and time needed. Moreover, a continuous data update for biodiversity monitoring purposes might be prohibitive. From this point of view, remote sensing represents a powerful tool since it allows to cover wide areas in a relatively low amount of time. One of the most common indicators of biodiversity is Shannon's entropy H′, which is strictly related to environmental heterogeneity, and thus to species diversity. However, Shannon's entropy might show drawbacks once applied to remote sensing data, since it considers relative abundances but it does not explicitly account for distances among pixels’ numerical values. In this paper we propose the use of Rao's Q applied to remotely sensed data, providing a straightforward R-package function to calculate it in 2D systems. We will introduce the theoretical rationale behind Rao's index and then provide applied examples based on the proposed R function

Rocchini, D.; Marcantonio, M.; Ricotta, C. (2017). Measuring Rao’s Q diversity index from remote sensing: an open source solution. ECOLOGICAL INDICATORS, 72: 234-238. doi: 10.1016/j.ecolind.2016.07.039 handle: http://hdl.handle.net/10449/34844

Measuring Rao’s Q diversity index from remote sensing: an open source solution

Rocchini, Duccio
Primo
;
Marcantonio, Matteo;
2017-01-01

Abstract

Measuring biodiversity is a key issue in ecology to guarantee effective indicators of ecosystem health at different spatial and time scales. However, estimating biodiversity from field observations might present difficulties related to costs and time needed. Moreover, a continuous data update for biodiversity monitoring purposes might be prohibitive. From this point of view, remote sensing represents a powerful tool since it allows to cover wide areas in a relatively low amount of time. One of the most common indicators of biodiversity is Shannon's entropy H′, which is strictly related to environmental heterogeneity, and thus to species diversity. However, Shannon's entropy might show drawbacks once applied to remote sensing data, since it considers relative abundances but it does not explicitly account for distances among pixels’ numerical values. In this paper we propose the use of Rao's Q applied to remotely sensed data, providing a straightforward R-package function to calculate it in 2D systems. We will introduce the theoretical rationale behind Rao's index and then provide applied examples based on the proposed R function
Biodiversity
Heterogeneity
Landscape metrics
Rao's Q
Remote sensing
Spatial ecology
Shannon's entropy
Settore BIO/03 - BOTANICA AMBIENTALE E APPLICATA
2017
Rocchini, D.; Marcantonio, M.; Ricotta, C. (2017). Measuring Rao’s Q diversity index from remote sensing: an open source solution. ECOLOGICAL INDICATORS, 72: 234-238. doi: 10.1016/j.ecolind.2016.07.039 handle: http://hdl.handle.net/10449/34844
File in questo prodotto:
File Dimensione Formato  
2017 EI Rocchini.pdf

solo utenti autorizzati

Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.6 MB
Formato Adobe PDF
1.6 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/34844
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 71
  • ???jsp.display-item.citation.isi??? 64
social impact