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Transferability of multi- and hyperspectral optical biocrust indices / Emilio Rodríguez-Caballero in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 94 – 107 Titre : Transferability of multi- and hyperspectral optical biocrust indices Type de document : Article/Communication Auteurs : Emilio Rodríguez-Caballero, Auteur ; P. Escribano, Auteur ; C. Olehowski, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 94 – 107 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse [Termes IGN] classification dirigée [Termes IGN] état de surface du sol [Termes IGN] image hyperspectrale [Termes IGN] indice de détection [Termes IGN] surface du sol Résumé : (auteur) Biological soil crusts (biocrusts) are communities of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, which live within or immediately on top of the uppermost millimeters of the soil in arid and semiarid regions. As biocrusts are highly relevant for ecosystem processes like carbon, nitrogen, and water cycling, a correct characterization of their spatial distribution is required. Following this objective, considerable efforts have been devoted to the identification and mapping of biocrusts using remote sensing data, and several mapping indices have been developed. However, their transferability to different regions has only rarely been tested. In this study we investigated the transferability of two multispectral indices, i.e. the Crust Index (CI) and the Biological Soil Crust Index (BSCI), and two hyperspectral indices, i.e. the Continuum Removal Crust Identification Algorithm (CRCIA) and the Crust Development Index (CDI), in three sites dominated by biocrusts, but with differences in soil and vegetation composition. Whereas multispectral indices have been important and valuable tools for first approaches to map and classify biological soil crusts, hyperspectral data and indices developed for these allowed to classify biocrusts at much higher accuracy. While multispectral indices showed Kappa (κ) values below 0.6, hyperspectral indices obtained good classification accuracy (κ ∼ 0.8) in both the study area where they had been developed and in the newly tested region. These results highlight the capability of hyperspectral sensors to identify specific absorption features related to photosynthetic pigments as chlorophyll and carotenoids, but also the limitation of multispectral information to discriminate between areas dominated by biocrusts, vegetation or bare soil. Based on these results we conclude that remote sensing offers an important and valid tool to map biocrusts. However, the spectral similarity between the main surface components of drylands and biocrusts demand for mapping indices based on hyperspectral information to correctly map areas dominated by biocrusts at ecosystem scale. Numéro de notice : A2017-115 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84510 [article]

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