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Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices / L. Ji in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 20 - 47 Titre : Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices Type de document : Article/Communication Auteurs : L. Ji, Auteur ; Li Zhang, Auteur ; Jennifer Rover, Auteur Année de publication : 2014 Article en page(s) : pp 20 - 47 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] bruit (théorie du signal) [Termes IGN] estimation statistique [Termes IGN] géostatistique [Termes IGN] indice de végétation Résumé : (Auteur) In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices. Numéro de notice : A2014-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73809 [article]

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