Publication: Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model
Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model
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Laurent, V. C. E., Verhoef, W., Schaepman, M. E., Damm, A., & Clevers, J. G. P. W. (2012). Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model. 2012 IEEE International Geoscience and Remote Sensing Symposium, 5685–5688. https://doi.org/10.1109/IGARSS.2012.6352321
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This contribution proposes a methodological approach based on a coupled canopy-atmosphere radiative transfer model and a Bayesian optimization algorithm, which allows the use of a priori data in the retrieval. This approach was used to estimate LAI and leaf chlorophyll content (Cab) in the agricultural test site Oensingen, Switzerland, from at-sensor radiance data of the new airborne APEX imaging spectrometer. The Bayesian optimization allowed having up to 7 free variables in the optimization. The obtained maps of estimated LAI and Ca
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- Laurent, Valérie C E
- Verhoef, W
- Clevers, J G P W
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Laurent, V. C. E., Verhoef, W., Schaepman, M. E., Damm, A., & Clevers, J. G. P. W. (2012). Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model. 2012 IEEE International Geoscience and Remote Sensing Symposium, 5685–5688. https://doi.org/10.1109/IGARSS.2012.6352321
