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Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects / Kiyun Yu in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 58 – 77 Titre : Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects Type de document : Article/Communication Auteurs : Kiyun Yu, Auteur ; Victoria Lenz-Wiedemann, Auteur ; X. Chen, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 58 – 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture de précision [Termes IGN] croissance des arbres [Termes IGN] exitance spectrale [Termes IGN] indice de végétation [Termes IGN] indice foliaire [Termes IGN] orge (céréale) [Termes IGN] réflectance spectrale [Termes IGN] surveillance de la végétation [Termes IGN] teneur en chlorophylle des feuilles Résumé : (Auteur) Monitoring in situ chlorophyll (Chl) content in agricultural crop leaves is of great importance for stress detection, nutritional state diagnosis, yield prediction and studying the mechanisms of plant and environment interaction. Numerous spectral indices have been developed for chlorophyll estimation from leaf- and canopy-level reflectance. However, in most cases, these indices are negatively affected by variations in canopy structure and soil background. The objective of this study was to develop spectral indices that can reduce the effects of varied canopy structure and growth stages for the estimation of leaf Chl. Hyperspectral reflectance data was obtained through simulation by a radiative transfer model, PROSAIL, and measurements from canopies of barley comprising different cultivars across growth stages using spectroradiometers. We applied a comprehensive band-optimization algorithm to explore five types of spectral indices: reflectance difference (RD), reflectance ratio (RR), normalized reflectance difference (NRD), difference of reflectance ratio (DRR) and ratio of reflectance difference (RRD). Indirectly using the multiple scatter correction (MSC) theory, we hypothesized that RRD can eliminate adverse effects of soil background, canopy structure and multiple scattering. Published indices and multivariate models such as optimum multiple band regression (OMBR), partial least squares regression (PLSR) and support vector machines for regression (SVR) were also employed. Results showed that the ratio of reflectance difference index (RRDI) optimized for simulated data significantly improved the correlation with Chl (R2 = 0.98, p Numéro de notice : A2014-524 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74136 [article]

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