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Bidirectional NDVI and atmospherically resistant BRDF inversion for vegetation canopy / F. Gao in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 40 n° 6 (June 2002) . - pp 1269 - 1278 Titre : Bidirectional NDVI and atmospherically resistant BRDF inversion for vegetation canopy Type de document : Article/Communication Auteurs : F. Gao, Auteur ; Y.J. Xiaowen, Auteur ; C.B. Schaaf, Auteur ; A. Strahler, Auteur Année de publication : 2002 Article en page(s) : pp 1269 - 1278 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection [Termes IGN] bande infrarouge [Termes IGN] bande rouge [Termes IGN] canopée [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] éclairement lumineux [Termes IGN] image optique [Termes IGN] image Terra-MODIS [Termes IGN] inversion [Termes IGN] modèle physique [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] spectroradiométrie Résumé : (Auteur) The normalized difference vegetation index (NDVI) has been widely applied in optical remote sensing. However, it has been demonstrated that NDVI is still partially affected by atmospheric path scattering and bidirectional (illumination and viewing geometry) effects. In this paper we present the benefit of using a bidirectional NDVI, and we discuss the problems in using the maximum NDVI composite method. Based on the assumption that a clear day has a larger NDVI value and a cloudy day has a smaller NDVI value (smaller reflectance in the nearinfrared band and larger reflectance in red band due to atmospheric path scattering), the ratio of squared observed NDVI values and calculated NDVI values is used as a weight in our inversion method. The calculated NDVI values are derived from previously inverted bidirectional reflectance distribution functions (BRDFs). The inversion process will loop until all weights converge. Our research on the early Terra/MODIS data using a semiempirical kerneldriven BRDF model (the RossThickLiTransit model) shows that this new method can improve inversion results whenever some cloudy pixels are not filtered out. As cloud detection and subpixel cloudiness are always a problem, this technique should still be very useful in improving the quality of BRDF inversion. Numéro de notice : A2002-187 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.800241 En ligne : https://ieeexplore.ieee.org/document/1020259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22102 [article]

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