This article describes the methods and problems associated to the estimation of canopy characteristics from remote sensing observations. It is illustrated over the solar spectral domain, with emphasis on LAI estimation using currently available algorithms developed for moderate resolution sensors. The principles of algorithms are first presented, distinguishing between canopy biophysical and radiometric data driven approaches that may use either radiative transfer models or experimental observations. Advantages and drawback are discussed with due attention to the operational character of the algorithms. Then the under-determination and ill-posedness nature of the inverse problem is described and illustrated. Finally, ways to improve the retrieval performances are presented, including the use of prior information, the exploitation of spatial and temporal constraints, and the interest in using holistic approaches based on the coupling of radiative transfer processes at several scales or levels. A conclusion is eventually proposed, discussing the three main components of retrieval approaches: retrieval techniques, radiative transfer models, and the exploitation of observations and ancillary information.
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Keywords
- Leaf Area Index
- Advance Very High Resolution Radiometer
- Advance Very High Resolution Radiometer
- Radiative Transfer Model
- Biophysical Variable
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Baret, F., Buis, S. (2008). Estimating Canopy Characteristics from Remote Sensing Observations: Review of Methods and Associated Problems. In: Liang, S. (eds) Advances in Land Remote Sensing. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6450-0_7
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