Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest Using a Triple-Source Leaf-Wood-Soil Layer Approach

Abstract

The fraction of absorbed photosynthetically active radiation (FAPAR) is generally divided into the fraction of radiation absorbed by the photosynthetic components (FAPAR green ) and the fraction of radiation absorbed by the non-photosynthetic components (FAPAR woody ) of the vegetation. However, most global FAPAR datasets do not take account of the woody components when considering the canopy radiation transfer. The objective of this study was to develop a generic algorithm for partitioning FAPAR canopy into FAPAR green and FAPAR woody based on a triple-source leaf-wood-soil layer (TriLay) approach. The LargE-Scale remote sensing data and image simulation framework (LESS) model was used to validate the TriLay approach. The results showed that the TriLay FAPAR green had higher retrieval accuracy, as well as a significantly lower bias (R 2 = 0.937, Root Mean Square Error (RMSE) = 0.064, and bias = −6.02% for black-sky conditions; R 2 = 0.997, RMSE = 0.025 and bias = −4.04% for white-sky conditions) compared to the traditional linear method (R 2 = 0.979, RMSE = 0.114, and bias = −18.04% for black-sky conditions; R 2 = 0.996, RMSE = 0.106 and bias = −16.93% for white-sky conditions). For FAPAR that did not take account of woody components (FAPAR noWAI ), the corresponding results were R 2 = 0.920, RMSE = 0.071, and bias = −7.14% for black-sky conditions, and R 2 = 0.999, RMSE = 0.043, and bias = −6.41% for white-sky conditions. Finally, the dynamic FAPAR green , FAPAR woody , FAPAR canopy and FAPAR noWAI products for a North America region were generated at a resolution of 500 m for every eight days in 2017. A comparison of the results for FAPAR green against those for FAPAR noWAI and FAPAR canopy showed that the discrepancy between FAPAR green and other FAPAR products for forest vegetation types could not be ignored. For deciduous needleleaf forest, in particular, the black-sky FAPAR green was found to contribute only about 23.86% and 35.75% of FAPAR canopy at the beginning and end of the year (from January to March and October to December, JFM and OND), and 75.02% at the peak growth stage (from July to September, JAS); the black-sky FAPAR noWAI was found to be overestimated by 38.30% and 28.46% during the early (JFM) and late (OND) part of the year, respectively. Therefore, the TriLay approach performed well in separating FAPAR green from FAPAR canopy , which is of great importance for a better understanding of the energy exchange within the canopy.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data

“…Simultaneously, it has been validated against the reference benchmark scenes provided by the International Radiation Transfer Model Initiative [ 45 ], demonstrating results that are comparable in accuracy and reliability to those of DART. LESS has also been applied for the algorithm validation of the retrieval of green vegetation fraction absorbed photosynthetically active radiation (FAPAR green ) [ 46 ], the evaluation of MODIS satellite LAI/FPAR algorithms [ 47 ], and the quantitative analysis of solar radiation over snow-covered mountains in the southeastern Tibetan Plateau [ 48 ]. In LESS, the simulation of APAR is primarily carried out through the forward ray tracing method.…”

Simulation-Based Evaluation of the Estimation Methods of Far-Red Solar-Induced Chlorophyll Fluorescence Escape Probability in Discontinuous Forest Canopies

“…However, fAPAR for whole canopy (i.e., fAPAR canopy ) generally can be divided into fAPAR for photosynthetic elements (i.e., fAPAR leaf ) and fAPAR for non-photosynthetic elements (i.e., fAPAR woody ), respectively [46,47]. The impact of fAPAR woody is neglected in most satellite-retrieved fAPAR products [48]. As a result, the direct use of satellite-retrieved fAPAR products (mostly fAPAR canopy ) to estimate SIF escape probability still needs further investigation [12,49].…”

Fractional Vegetation Cover Derived from UAV and Sentinel-2 Imagery as a Proxy for In Situ FAPAR in a Dense Mixed-Coniferous Forest?

“…For its key role in ecosystem processes and productivity, it is listed as one of the terrestrial Essential Climate Variables (ECVs) by the GCOS [5,6]. Satellite remote sensing provides spatially distributed information on vegetation spectral properties, and numerous retrieval algorithms have been developed to retrieve FAPAR from space [7][8][9][10][11][12]. Thus, there is an increasing availability of FAPAR datasets from hectometric (Terra & Aqua/MODIS [13], SPOT/VEGETATION [14], PROBA-V [15] and Sentinel-3/OLCI [16]) to decametric (Sentinel-2/MSI [17]) spatial resolutions.…”