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Forest beta-diversity analysis by remote sensing: How scale and sensors affect the Rao’s Q index

Khare Siddhartha, Latifi Hooman et Rossi Sergio. (2019). Forest beta-diversity analysis by remote sensing: How scale and sensors affect the Rao’s Q index. Ecological Indicators, 106, e105520.

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Space-borne remote sensing missions provide robust, timely and continuous data to assess biodiversity in remote or protected areas, where direct field observations can be prohibited by difficult accessibility. The objective of this study was to extend the concept of remote sensing based assessment of beta-diversity to multi-scale domain by multi-resolution optical satellite data. This study was conducted in a reserved forest of western Himalaya, India; a region affected by the invasive Lantana camara L (lantana). We calculated and compared Rao’s Q and Shannon indices at different spatial resolutions (0.5, 5, and 30 m) and scales (window sizes) by using imageries from Pléiades 1A, RapidEye, and Landsat-8 acquired in April 2013, the pre-monsoon season. Rao’s Q index explained diversity more accurately than Shannon index for the three analyzed stand densities. Diversity was better approximated by Rao’s Q index calculated by Pléiades 1A at a resolution of 0.5 m at low stand density. We observed higher correlations of the average coefficient of variation (CV) with Rao’s Q and Shannon indices for areas associated with mixed spectral reflectance caused by overstory and understory vegetation. Furthermore, CV was lower in open areas dominated by lantana. These results indicated a strong scale and spatial resolution dependence of Rao’s Q index on remote sensing-derived spectral heterogeneity information. When applied in heterogeneous forest environments, Rao’s Q index could represent a better remote sensing proxy to estimate beta-diversity than the conventional Shannon index.

Type de document:Article publié dans une revue avec comité d'évaluation
Version évaluée par les pairs:Oui
Identifiant unique:10.1016/j.ecolind.2019.105520
Sujets:Sciences naturelles et génie > Sciences appliquées > Foresterie et sciences du bois
Sciences naturelles et génie > Sciences naturelles > Biologie et autres sciences connexes
Département, module, service et unité de recherche:Unités de recherche > Centre de recherche sur la Boréalie (CREB)
Départements et modules > Département des sciences fondamentales
Mots-clés:Rao’s Q and Shannon indices, invasive species, biodiversity, beta-diversity, remote sensing, pléiades 1A, rapidEye, Landsat-8
Déposé le:05 juin 2023 12:53
Dernière modification:05 juin 2023 12:53
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