Leaf pigment retrieval using the PROSAIL model: Influence of uncertainty in prior canopy-structure information
Jia Sun,
Lunche Wang,
Shuo Shi,
Zhenhai Li,
Jian Yang,
Wei Gong,
Shaoqiang Wang,
Torbern Tagesson
Affiliations
Jia Sun
Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geoscience, Wuhan 430079, Hubei, China; Department of Physical Geography and Ecosystem Science, Lund University, Lund 117 SE-22100, Sweden
Lunche Wang
Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geoscience, Wuhan 430079, Hubei, China; Corresponding author.
Shuo Shi
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, Hubei, China
Zhenhai Li
Key Laboratory of Quantitative Remote Sensing in Ministry of Agriculture and Rural Affairs, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
Jian Yang
Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geoscience, Wuhan 430079, Hubei, China
Wei Gong
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, Hubei, China
Shaoqiang Wang
Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geoscience, Wuhan 430079, Hubei, China
Torbern Tagesson
Department of Physical Geography and Ecosystem Science, Lund University, Lund 117 SE-22100, Sweden; Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1172, Denmark
Leaf pigments are critical indicators of plant photosynthesis, stress, and physiological conditions. Inversion of radiative transfer models (RTMs) is a promising method for robustly retrieving leaf biochemical traits from canopy observations, and adding prior information has been effective in alleviating the “ill-posed” problem, a major challenge in model inversion. Canopy structure parameters, such as leaf area index (LAI) and average leaf inclination angle (ALA), can serve as prior information for leaf pigment retrieval. Using canopy spectra simulated from the PROSAIL model, we estimated the effects of uncertainty in LAI and ALA used as prior information for lookup table-based inversions of leaf chlorophyll (Cab) and carotenoid (Car). The retrieval accuracies of the two pigments were increased by use of the priors of LAI (RMSE of Cab from 7.67 to 6.32 μg cm−2, Car from 2.41 to 2.28 μg cm−2) and ALA (RMSE of Cab from 7.67 to 5.72 μg cm−2, Car from 2.41 to 2.23 μg cm−2). However, this improvement deteriorated with an increase of additive and multiplicative uncertainties, and when 40% and 20% noise was added to LAI and ALA respectively, these priors ceased to increase retrieval accuracy. Validation using an experimental winter wheat dataset also showed that compared with Car, the estimation accuracy of Cab increased more or deteriorated less with uncertainty in prior canopy structure. This study demonstrates possible limitations of using prior information in RTM inversions for retrieval of leaf biochemistry, when large uncertainties are present.
