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An Open Data Approach for Estimating Vegetation Gross Primary . . . In this study, based on the Eddy Covariance-Light Use Efficiency (EC-LUE) model, we used Google Earth Engine (GEE) to develop a web application (EC-LUE APP) to generate 30-m-spatial-resolution GPP estimates within a region of interest
Vegetation Photosynthesis Model v3. 0: Improved Estimates of Terrestrial . . . Here, we introduce an improved Vegetation Photosynthesis Model (VPM v3 0), which incorporates site-specific apparent optimum temperature for photosynthesis, leaf-trait-based light absorption (flat leaf vs needle leaf), and improved water stress estimation
Global-scale improvement of terrestrial gross primary productivity . . . Sunlight-induced chlorophyll fluorescence (SIF), as the core variable, outperforms traditional vegetation indices and helps estimate gross primary productivity (GPP) more accurately The fusion of multi-source data enhances the model’s adaptability, especially in complex ecosystems
Improving global gross primary productivity estimation by fusing multi . . . In this study, we improve the quantification of global gross primary productivity by integrating multiple source GPP products without using any prior knowledge through the Bayesian-based Three-Cornered Hat (BTCH) method to generate a new weighted GPP data set
Estimation of Gross Primary Productivity (GPP) of Global Terrestrial . . . Estimating global terrestrial Gross Primary Productivity (GPP) through process-based models is challenging due to complex parameterization,while data-driven models and light-use efficiency models rely heavily on extensive datasets The significant spatial heterogeneity of terrestrial ecosystems also limits the application of these three major
A critical review of methods, principles and progress for estimating . . . In this study, we reviewed studies of GPP estimation at different spatiotemporal scales, and systematically reviewed the principles, formulas, representative methods (Ground observations, Model simulations, SIF based GPP, and NIRv based GPP) at different scales and models (Statistical Ecological process Machine learning Light use efficiency mode
Long-term Simulation of Gross Primary Productivity and its Impact . . . In this study, we combined a mechanistic model with a data-driven model for Gross Primary Productivity (GPP) simulation (Fig 1) The core innovation lies in integrating the physical mechanisms of process-based models with the nonlinear representation capabilities of data-driven models