The Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is essential for assessing vegetation's photosynthetic efficiency and ecosystem energy balance. While the MODIS FPAR product provides valuable global data, its reliability is compromised by noise, particularly under poor observation conditions like cloud cover. To solve this problem, we developed the Spatio-Temporal Information Composition Algorithm (STICA), which enhances MODIS FPAR by integrating quality control, spatio-temporal correlations, and original FPAR values, resulting in the High-Quality FPAR (HiQ-FPAR) product.
View Article and Find Full Text PDFThe fraction of absorbed photosynthetically active radiation (FPAR) is an essential biophysical parameter that characterizes the structure and function of terrestrial ecosystems. Despite the extensive utilization of several satellite-derived FPAR products, notable temporal inconsistencies within each product have been underscored. Here, the new generation of the GIMMS FPAR product, GIMMS FPAR4g, was developed using a combination of a machine learning algorithm and a pixel-wise multi-sensor records integration approach.
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