scholarly journals Impact of Modeling Abstractions When Estimating Leaf Mass per Area and Equivalent Water Thickness Over Sparse Forests Using a Hybrid Method

2021 ◽  
Vol 13 (16) ◽  
pp. 3235
Author(s):  
Thomas Miraglio ◽  
Margarita Huesca ◽  
Jean-Philippe Gastellu-Etchegorry ◽  
Crystal Schaaf ◽  
Karine R. M. Adeline ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Fire Risk ◽  
Leaf Mass Per Area ◽  
Spectral Interval ◽  
Calibration Data ◽  
Scene Modeling ◽  
Potential Growth ◽  
Tree Crowns ◽  
Leaf Mass ◽  
Equivalent Water Thickness

Equivalent water thickness (EWT) and leaf mass per area (LMA) are important indicators of plant processes, such as photosynthetic and potential growth rates and health status, and are also important variables for fire risk assessment. Retrieving these traits through remote sensing is challenging and often requires calibration with in situ measurements to provide acceptable results. However, calibration data cannot be expected to be available at the operational level when estimating EWT and LMA over large regions. In this study, we assessed the ability of a hybrid retrieval method, consisting of training a random forest regressor (RFR) over the outputs of the discrete anisotropic radiative transfer (DART) model, to yield accurate EWT and LMA estimates depending on the scene modeling within DART and the spectral interval considered. We show that canopy abstractions mostly affect crown reflectance over the 0.75–1.3 μm range. It was observed that excluding these wavelengths when training the RFR resulted in the abstraction level having no effect on the subsequent LMA estimates (RMSE of 0.0019 g/cm2 for both the detailed and abstract models), and EWT estimates were not affected by the level of abstraction. Over AVIRIS-Next Generation images, we showed that the hybrid method trained with a simplified scene obtained accuracies (RMSE of 0.0029 and 0.0028 g/cm2 for LMA and EWT) consistent with what had been obtained from the test dataset of the calibration phase (RMSE of 0.0031 and 0.0032 g/cm2 for LMA and EWT), and the result yielded spatially coherent maps. The results demonstrate that, provided an appropriate spectral domain is used, the uncertainties inherent to the abstract modeling of tree crowns within an RTM do not significantly affect EWT and LMA accuracy estimates when tree crowns can be identified in the images.

scholarly journals Joint Use of PROSAIL and DART for Fast LUT Building: Application to Gap Fraction and Leaf Biochemistry Estimations over Sparse Oak Stands

2020 ◽  
Vol 12 (18) ◽  
pp. 2925
Author(s):  
Thomas Miraglio ◽  
Karine Adeline ◽  
Margarita Huesca ◽  
Susan Ustin ◽  
Xavier Briottet
Keyword(s):  
Mean Squared Error ◽  
Approximation Error ◽  
High Sensitivity ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Leaf Mass Per Area ◽  
Approximation Model ◽  
Equivalent Water Thickness ◽  
Gap Fraction ◽  
Chlorophylls A And B

Gap Fraction, leaf pigment contents (content of chlorophylls a and b (Cab) and carotenoids content (Car)), Leaf Mass per Area (LMA), and Equivalent Water Thickness (EWT) are considered relevant indicators of forests’ health status, influencing many biological and physical processes. Various methods exist to estimate these variables, often relying on the extensive use of Radiation Transfer Models (RTMs). While 3D RTMs are more realistic to model open canopies, their complexity leads to important computation times that limit the number of simulations that can be considered; 1D RTMs, although less realistic, are also less computationally expensive. We investigated the possibility to approximate the outputs of a 3D RTM (DART) from a 1D RTM (PROSAIL) to generate in very short time numerous extensive Look-Up Tables (LUTs). The intrinsic error of the approximation model was evaluated through comparison with DART reference values. The model was then used to generate LUTs used to estimate Gap Fraction, Cab, Car, EWT, and LMA of Blue Oak-dominant stands in a woodland savanna from AVIRIS-C data. Performances of the approximation model for estimation purposes compared to DART were evaluated using Wilmott’s index of agreement (dr), and estimation accuracy was measured with coefficients of determination (R2) and Root Mean Squared Error (RMSE). The low approximation error of the proposed model demonstrated that the model could be considered for canopy covers as low as 30%. Gap Fraction estimations presented similar performances with either DART or the approximation (dr 0.78 and 0.77, respectively), while Cab and Car showed improved performances (dr increasing from 0.65 to 0.77 and 0.34 to 0.65, respectively). No satisfying estimation methods were found for LMA and EWT using either models, probably due to the high sensitivity of the scene’s reflectance to Gap Fraction and soil modeling at such low LAI. Overall, estimations using the approximated reflectances presented either similar or improved accuracy. Our findings show that it is possible to approximate DART reflectances from PROSAIL using a minimal number of DART outputs for calibration purposes, drastically reducing computation times to generate reflectance databases: 300,000 entries could be generated in 1.5 h, compared to the 12,666 total CPU hours necessary to generate the 21,840 calibration entries with DART.

Photosynthesis and physiological traits of evergreen broadleafed saplings during winter under different light environments in a temperate forest

2006 ◽  
Vol 84 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Yoshiyuki Miyazawa ◽  
Kihachiro Kikuzawa
Keyword(s):  
Temperate Forest ◽  
Light Availability ◽  
Net Photosynthesis ◽  
Carbon Gain ◽  
Leaf Mass Per Area ◽  
Camellia Japonica ◽  
Leaf Mass ◽  
Unit Leaf ◽  
Canopy Trees ◽  
Photosynthetic Traits

Photosynthetic traits of the evergreen broadleafed species Camellia japonica L. and Quercus glauca Thunb. were continuously investigated during autumn and winter using saplings that grew in different light environments (gap, deciduous canopy understory, and evergreen canopy understory) in a temperate forest. Light-saturated rates of net photosynthesis in midwinter and spring were lower than those in autumn. Photosynthetic capacity, scaled to a common leaf temperature of 25 °C, increased or remained stable after autumn and then decreased in spring in most leaves. Photosynthetic traits per unit leaf area were different among leaves in different light environments of both Camellia and Quercus during most periods. However, photosynthetic traits per unit leaf mass did not differ among leaves in different light environments, suggesting that differences in photosynthetic traits were mainly due to different leaf mass per area among leaves. Photosynthetic rates under light availability typical in the environment were lower in winter than in autumn in leaves in the sun in a gap but were not different in leaves in the shade under evergreen canopy trees. Thus, the importance of winter carbon gain for annual carbon gain is small in leaves in a gap but is large in leaves under evergreen canopy trees.

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