Barbier Nicolas auteur aut IRD Couteron Pierre auteur aut IRD Gastelly-Etchegorry J. P. auteur aut IRD Proisy Christophe auteur aut IRD text journalArticle eng text/pdf born digital access Context Remote sensing methods, and in particular very high (metric) resolution optical imagery, are essential assets to obtain forest structure data that cannot be measured from the ground because they are too difficult to measure or because the areas to sample are too large or inaccessible. Aim To understand what kind of, and how precisely and accurately, information on forest structure can be inverted from RS data, we propose a modeling framework allowing to produce forest canopy images for any type of forest based on basic inventory data. Methods This framework combines a simple 3D forest model named "Allostand," based on empirically or theoretically derived diameter at breast height distributions and allometry rules, with a well-established radiative transfer model, discrete anisotropic radiative transfer. Results Resulting simulated images appear of good realism for textural analysis. The potential of the approach for the development of quantitative methods to assess forest structure, dynamics, matter and energy budgets, and degradation, including in tropical contexts, is illustrated emphasizing broad-leaved natural forests. Conclusion Consequently, this theoretical framework appears as a valuable component for developing inversion methods from canopy images and studying their sensitivity to structural and instrumental effects. specialized Texture analysis Remote sensing 3D forest model Radiative transfer model Broad-leaved tropical forests 082 020 126 69 2 305-311 2012 1286-4560 https://www.documentation.ird.fr/hor/fdi:010055838 10.1007/s13595-011-0116-9 1286-4560 [F B010055838] https://www.documentation.ird.fr/hor/fdi:010055838 https://www.documentation.ird.fr/intranet/publi/2012/05/010055838.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2012-06-01 2017-08-23 fdi:010055838 fre