Improvements of the MODIS Gross Primary Productivity model based on a comprehensive uncertainty assessment over the Brazilian Amazonia

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 145; pp. 268 - 283
• Main Authors: Almeida, Catherine Torres de, Delgado, Rafael Coll, Galvão, Lênio Soares, Aragão, Luiz Eduardo de Oliveira Cruz e, Ramos, María Concepción
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-11-2018
• Subjects: Amazon; Light use efficiency; MOD17A2; Savanna; Validation; Validation; Light use efficiency; Amazon; MOD17A2; Savanna
• ISSN: 0924-2716; 1872-8235
• DOI: 10.1016/j.isprsjprs.2018.07.016

•MOD17 GPP collections were evaluated against eddy covariance data for tropical sites.•Inaccuracies in magnitude and seasonality of GPP in the studied region were found.•Use of site-specific input data did not consistently improve GPP estimates.•Better GPP estimations in tropical forests require changes in the MOD17 algorithm.•Using a separate LUE for cloudy and clear sky conditions showed the best performance.
Tropical forests and savannas are responsible for the largest proportion of global Gross Primary Productivity (GPP), a major component of the global carbon cycle. However, there are still deficiencies in the spatial and temporal information of tropical photosynthesis and its relations with environmental controls. The MOD17 product, based on the Light Use Efficiency (LUE) concept, has been updated to provide GPP estimates around the globe. In this research, the MOD17 GPP collections 5.0, 5.5 and 6.0 and their sources of uncertainties were assessed by using measurements of meteorology and eddy covariance GPP from eight flux towers in Brazilian tropical ecosystems, from 2000 to 2006. Results showed that the MOD17 collections tend to overestimate GPP at low productivity sites (bias between 111% and 584%) and underestimate it at high productivity sites (bias between −2% and −18%). Overall, the MOD17 product was not able to capture the GPP seasonality, especially in the equatorial sites. Recalculations of MOD17 GPP using site-specific meteorological data, corrected land use/land cover (LULC) classification, and tower-based LUE parameter showed improvements for some sites. However, the improvements were not sufficient to estimate the GPP seasonality in the equatorial forest sites. The use of a new soil moisture constraint on the LUE, based on the Evaporative Fraction, just showed improvements in water-limited sites. Modifications in the algorithm to account for separate LUE for cloudy and clear sky days presented noticeably improved GPP estimates in the tropical ecosystems investigated, both in magnitude and in seasonality. The results suggest that the high cloudiness makes the diffuse radiation an important factor to be considered in the LUE control, especially over dense forests. Thus, the MOD17 GPP algorithm needs more updates to accurately estimate productivity in tropical ecosystems.