Abstract
• 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.
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Acknowledgments
We wish to thank one anonymous reviewer for his careful revision.
Funding
This work has been supported by the Centre National d’Etudes Spatiales for the preparation of the “Pleiades” mission, by INRA through a post-doctoral grant, and by a Marie Curie IEF FP7 grant of the European Union.
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Barbier, N., Couteron, P., Gastelly-Etchegorry, JP. et al. Linking canopy images to forest structural parameters: potential of a modeling framework. Annals of Forest Science 69, 305–311 (2012). https://doi.org/10.1007/s13595-011-0116-9
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DOI: https://doi.org/10.1007/s13595-011-0116-9