{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T22:39:11Z","timestamp":1767998351478,"version":"3.49.0"},"reference-count":102,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T00:00:00Z","timestamp":1615161600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2017YFB0503500"],"award-info":[{"award-number":["2017YFB0503500"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41930104"],"award-info":[{"award-number":["41930104"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Natural Science Foundation of Jiangsu Province","award":["SBK2019022628"],"award-info":[{"award-number":["SBK2019022628"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurately and reliably estimating total terrestrial gross primary production (GPP) on a large scale is of great significance for monitoring the carbon cycle process. The Sentinel-3 satellite provides the OLCI FAPAR and OTCI products, which possess a higher spatial and temporal resolution than MODIS products. However, few studies have focused on using LUE models and VI-driven models based on the Sentinel-3 satellites to estimate GPP on a large scale. The purpose of this study is to evaluate the performance of Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data in estimating GPP at site and regional scale. Firstly, we integrated OLCI FAPAR and meteorology reanalysis data into the MODIS GPP algorithm and eddy covariance light use efficiency (EC-LUE) model (GPPMODIS-GPP and GPPEC-LUE, respectively). Then, we combined OTCI and meteorology reanalysis data with the greenness and radiation (GR) model and vegetation index (VI) model (GPPGR and GPPVI, respectively). Lastly, GPPMODIS-GPP, GPPEC-LUE, GPPGR, and GPPVI were evaluated against the eddy covariance flux data (GPPEC) at the site scale and MODIS GPP products (GPPMOD17) at the regional scale. The results showed that, at the site scale, GPPMODIS-GPP and GPPEC-LUE agreed well with GPPEC for the US-Ton site, with R2 = 0.73 and 0.74, respectively. The performance of GPPGR and GPPVI varied across different biome types. Strong correlations were obtained across deciduous broadleaf forests, mixed forests, grasslands, and croplands. At the same time, there are overestimations and underestimations in croplands, evergreen needleleaf forests and deciduous broadleaf forests. At the regional scale, the annual mean and maximum daily GPPMODIS-GPP and GPPEC-LUE agreed well with GPPMOD17 in 2017 and 2018, with R2 &gt; 0.75. Overall, the above findings demonstrate the feasibility of using Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data through LUE and VI-driven models to estimate GPP, and fill in the gaps for the large-scale evaluation of GPP via Sentinel-3 satellites.<\/jats:p>","DOI":"10.3390\/rs13051015","type":"journal-article","created":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T12:12:18Z","timestamp":1615205538000},"page":"1015","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Integration of Sentinel-3 OLCI Land Products and MERRA2 Meteorology Data into Light Use Efficiency and Vegetation Index-Driven Models for Modeling Gross Primary Production"],"prefix":"10.3390","volume":"13","author":[{"given":"Fengji","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhijiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Long","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3228-8374","authenticated-orcid":false,"given":"Ling","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"170165","DOI":"10.1038\/sdata.2017.165","article-title":"A global moderate resolution dataset of gross primary production of vegetation for 2000\u20132016","volume":"4","author":"Zhang","year":"2017","journal-title":"Sci. Data"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1126\/science.1184984","article-title":"Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate","volume":"329","author":"Beer","year":"2010","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chapin, F.S., Matson, P.A., and Vitousek, P.M. (2011). Principles of Terrestrial Ecosystem Ecology, Springer.","DOI":"10.1007\/978-1-4419-9504-9"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3731","DOI":"10.1111\/gcb.14729","article-title":"Terrestrial gross primary production: Using NIRV to scale from site to globe","volume":"25","author":"Badgley","year":"2019","journal-title":"Global Chang. Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1016\/j.rse.2010.07.012","article-title":"Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest","volume":"114","author":"Wu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1016\/j.agrformet.2008.06.015","article-title":"Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data","volume":"148","author":"Xiao","year":"2008","journal-title":"Agric. For. Meteorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1000472717236","article-title":"Flux Footprints Within and Over Forest Canopies","volume":"85","author":"Baldocchi","year":"1997","journal-title":"Bound. Layer Meteorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1007\/BF00713146","article-title":"Source areas for scalars and scalar fluxes","volume":"67","author":"Schmid","year":"1994","journal-title":"Bound. Layer Meteorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5263","DOI":"10.1029\/93JD03221","article-title":"Methodology for the estimation of terrestrial net primary production from re-motely sensed data","volume":"9","author":"Ruimy","year":"1994","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lieth, H., and Whittaker, R.H. (1975). Modeling the Primary Productivity of the World. Primary Productivity of the Biosphere, Springer.","DOI":"10.1007\/978-3-642-80913-2"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Lieth, H., and Whittaker, R.H. (1975). Quantitative Evaluation of Global Primary Productivity Models Generated by Computers. Primary Productivity of the Biosphere, Springer.","DOI":"10.1007\/978-3-642-80913-2"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"343","DOI":"10.2480\/agrmet.40.343","article-title":"Agroclimatic Evaluation of Net Primary Productivity of Natural Vegetations. (1) Chikugo Model for Evaluating Net Primary Productivity","volume":"40","author":"Uchijima","year":"1985","journal-title":"J. Agric. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Jung, M., Reichstein, M., Margolis, H.A., Cescatti, A., Richardson, A.D., Arain, M.A., Arneth, A., Bernhofer, C., Bonal, D., and Chen, J. (2011). Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. Biogeosci., 116.","DOI":"10.1029\/2010JG001566"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1029\/96GB02692","article-title":"An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics","volume":"10","author":"Foley","year":"1996","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1046\/j.1365-2486.2003.00569.x","article-title":"Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model","volume":"9","author":"Sitch","year":"2003","journal-title":"Glob. Chang. Biol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0304-3800(96)00034-8","article-title":"A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3.0)","volume":"95","author":"Friend","year":"1997","journal-title":"Ecol. Model."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1046\/j.1365-2486.1999.00009.x","article-title":"Comparing global models of terrestrial net primary productivity (NPP): Overview and key results","volume":"5","author":"Cramer","year":"1999","journal-title":"Glob. Chang. Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"03010","DOI":"10.1029\/2012JG001960","article-title":"A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis","volume":"117","author":"Schaefer","year":"2012","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1016\/j.scitotenv.2019.03.025","article-title":"Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variabil-ity and CO2 trends","volume":"668","author":"Sun","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2594","DOI":"10.1126\/science.1055071","article-title":"Biospheric Primary Production During an ENSO Transition","volume":"291","author":"Behrenfeld","year":"2001","journal-title":"Science"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2725","DOI":"10.5194\/essd-12-2725-2020","article-title":"Improved estimate of global gross primary production for reproducing its long-term variation, 1982\u20132017","volume":"12","author":"Zheng","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.agrformet.2014.03.007","article-title":"Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database","volume":"192\u2013193","author":"Yuan","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.rse.2007.08.004","article-title":"A new model of gross primary productivity for North American ecosystems based solely on the en-hanced vegetation index and land surface temperature from MODIS","volume":"112","author":"Sims","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","first-page":"1","article-title":"Remote estimation of grassland gross primary production during extreme meteorological seasons","volume":"29","author":"Rossini","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"747","DOI":"10.2307\/2401901","article-title":"Solar Radiation and Productivity in Tropical Ecosystems","volume":"9","author":"Monteith","year":"1972","journal-title":"J. Appl. Ecol."},{"key":"ref_26","first-page":"277","article-title":"Climate and the Efficiency of Crop Production in Britain [and Discussion]. Philosophi-cal Transactions of the Royal Society of London","volume":"281","author":"Monteith","year":"1977","journal-title":"Ser. B Biol. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1029\/93GB02725","article-title":"Terrestrial ecosystem production: A process model based on global satellite and surface data","volume":"7","author":"Potter","year":"1993","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1641\/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2","article-title":"A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production","volume":"54","author":"Running","year":"2004","journal-title":"Bioscience"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"815","DOI":"10.2307\/2845983","article-title":"Global Primary Production: A Remote Sensing Approach","volume":"22","author":"Prince","year":"1995","journal-title":"J. Biogeogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/S0034-4257(02)00043-3","article-title":"Estimation of carbon mass fluxes over Europe using the C-Fix model and Euroflux data","volume":"83","author":"Veroustraete","year":"2002","journal-title":"Remote. Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.rse.2004.03.010","article-title":"Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data","volume":"91","author":"Xiao","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.agrformet.2006.12.001","article-title":"Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross pri-mary production across biomes","volume":"143","author":"Yuan","year":"2007","journal-title":"Agric. Forest Meteorol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"111686","DOI":"10.1016\/j.rse.2020.111686","article-title":"The potential of satellite FPAR product for GPP estimation: An indirect evaluation using so-lar-induced chlorophyll fluorescence","volume":"240","author":"Zhang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2014.07.012","article-title":"Estimation of crop gross primary production (GPP): fAPARchl versus MOD15A2 FPAR","volume":"153","author":"Zhang","year":"2014","journal-title":"Remote. Sens. Environ."},{"key":"ref_35","first-page":"195","article-title":"Relationship between atmospheric CO2 variations and a satellite-derived vegetation index","volume":"319","author":"Tucker","year":"1986","journal-title":"Nat. Cell Biol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2013.01.010","article-title":"Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements","volume":"132","author":"Hmimina","year":"2013","journal-title":"Remote. Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Huang, X., Xiao, J., and Ma, M. (2019). Evaluating the Performance of Satellite-Derived Vegetation Indices for Estimating Gross Primary Productivity Using FLUXNET Observations across the Globe. Remote. Sens., 11.","DOI":"10.3390\/rs11151823"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Almond, S., Boyd, D.S., Dash, J., Curran, P.J., Hill, R.A., and Foody, G.M. (2010). Estimating terrestrial gross primary productivity with the Envisat Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI). IEEE Int. Geosci. Remote Sens. Symp., 4792\u20134795.","DOI":"10.1109\/IGARSS.2010.5654088"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Lin, S., Li, J., Liu, Q., Li, L., Zhao, J., and Yu, W. (2019). Evaluating the Effectiveness of Using Vegetation Indices Based on Red-Edge Reflectance from Sentinel-2 to Estimate Gross Primary Productivity. Remote. Sens., 11.","DOI":"10.3390\/rs11111303"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Nestola, E., Calfapietra, C., Emmerton, C.A., Wong, C.Y., Thayer, D.R., and Gamon, J.A. (2016). Monitoring Grassland Seasonal Carbon Dynamics, by Integrating MODIS NDVI, Proximal Optical Sampling, and Eddy Covariance Measurements. Remote. Sens., 8.","DOI":"10.3390\/rs8030260"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"301","DOI":"10.5589\/m10-050","article-title":"Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy meas-urements","volume":"36","author":"Wu","year":"2010","journal-title":"Can. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Wu, C., Niu, Z., and Gao, S. (2010). Gross primary production estimation from MODIS data with vegetation index and pho-tosynthetically active radiation in maize. J. Geophys. Res. Atmos., 115.","DOI":"10.1029\/2009JD013023"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Wang, H., Li, X., Ma, M., and Geng, L. (2019). Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach. Remote Sens., 11.","DOI":"10.3390\/rs11030225"},{"key":"ref_44","first-page":"234","article-title":"Overview on estimation accuracy of gross primary productivity with remote sensing methods","volume":"22","author":"Lin","year":"2018","journal-title":"Yaogan Xuebao J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.1109\/TGRS.2005.853936","article-title":"Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations","volume":"44","author":"Heinsch","year":"2006","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.isprsjprs.2013.10.015","article-title":"The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation","volume":"88","author":"Wu","year":"2014","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3424","DOI":"10.1016\/j.rse.2011.08.006","article-title":"Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration","volume":"115","author":"Wu","year":"2011","journal-title":"Remote. Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2015.02.022","article-title":"Comparison of four EVI-based models for estimating gross primary production of maize and soybean croplands and tallgrass prairie under severe drought","volume":"162","author":"Dong","year":"2015","journal-title":"Remote. Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1016\/j.rse.2010.03.010","article-title":"The potential of the MERIS Terrestrial Chlorophyll Index for carbon flux estimation","volume":"114","author":"Harris","year":"2010","journal-title":"Remote. Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Zhao, L., and Lin, A. (2020). Evaluating the Performance of Sentinel-3A OLCI Land Products for Gross Primary Productivity Estimation Using AmeriFlux Data. Remote. Sens., 12.","DOI":"10.3390\/rs12121927"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Wang, X., Ling, F., Yao, H., Liu, Y., and Xu, S. (2019). Unsupervised Sub-Pixel Water Body Mapping with Sentinel-3 OLCI Image. Remote. Sens., 11.","DOI":"10.3390\/rs11030327"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Neneman, M., Wagner, S., Bourg, L., Blanot, L., Bouvet, M., Adriaensen, S., and Nieke, J. (2020). Use of Moon Observations for Characterization of Sentinel-3B Ocean and Land Color Instrument. Remote Sens., 12.","DOI":"10.3390\/rs12162543"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Lamquin, N., Clerc, S., Bourg, L., and Donlon, C. (2020). OLCI A\/B Tandem Phase Analysis, Part 1: Level 1 Homogenisation and Harmonisation. Remote. Sens., 12.","DOI":"10.3390\/rs12111804"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Nieke, J., and Mavrocordatos, C. (2017). Sentinel-3a: Commissioning phase results of its optical payload. Int. Conf. Space Opt., 187.","DOI":"10.1117\/12.2296174"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Pastor-Guzman, J., Brown, L., Morris, H., Bourg, L., Goryl, P., Dransfeld, S., and Dash, J. (2020). The Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI): Algorithm Improvements, Spatiotemporal Consistency and Continuity with the MERIS Archive. Remote. Sens., 12.","DOI":"10.3390\/rs12162652"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"413","DOI":"10.3319\/TAO.2012.03.12.01(A)","article-title":"Characterizing Spatial-Temporal Variations in Vegetation Phenology over the North-South Transect of Northeast Asia Based upon the MERIS Terrestrial Chlorophyll Index","volume":"23","author":"Jin","year":"2012","journal-title":"Terr. Atmos. Ocean. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.rse.2011.07.023","article-title":"ESA\u2019s sentinel missions in support of Earth system science","volume":"120","author":"Berger","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1029\/2004JG000004","article-title":"Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses","volume":"111","author":"Zhao","year":"2006","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Wang, L., Zhu, H., Lin, A., Zou, L., Qin, W., and Du, Q. (2017). Evaluation of the Latest MODIS GPP Products across Multiple Biomes Using Global Eddy Covariance Flux Data. Remote Sens., 9.","DOI":"10.3390\/rs9050418"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.rse.2004.12.011","article-title":"Improvements of the MODIS terrestrial gross and net primary production global data set","volume":"95","author":"Zhao","year":"2005","journal-title":"Remote. Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2016.05.015","article-title":"Consistency between sun-induced chlorophyll fluorescence and gross primary production of vegeta-tion in North America","volume":"183","author":"Zhang","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1016\/j.rse.2011.02.019","article-title":"Improvements to a MODIS global terrestrial evapotranspiration algorithm","volume":"115","author":"Mu","year":"2011","journal-title":"Remote. Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1111\/j.1365-2486.2005.001002.x","article-title":"On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm","volume":"11","author":"Reichstein","year":"2005","journal-title":"Glob. Chang. Biol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"5015","DOI":"10.5194\/bg-15-5015-2018","article-title":"Basic and extensible post-processing of eddy covariance flux data with REddyProc","volume":"15","author":"Wutzler","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1002\/2013JG002597","article-title":"Ecosystem CO2\/H2O fluxes are explained by hydraulically limited gas exchange during tree mor-tality from spruce bark beetles","volume":"119","author":"Frank","year":"2014","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.agrformet.2004.06.008","article-title":"Carbon exchange and venting anomalies in an upland deciduous forest in northern Wisconsin, USA","volume":"126","author":"Cook","year":"2004","journal-title":"Agric. For. Meteorol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.agrformet.2014.10.017","article-title":"Landscape-level terrestrial methane flux observed from a very tall tower","volume":"201","author":"Desai","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1007\/s10021-019-00400-x","article-title":"Water and Carbon Fluxes Along an Elevational Gradient in a Sagebrush Ecosystem","volume":"23","author":"Flerchinger","year":"2020","journal-title":"Ecosystems"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.agrformet.2016.07.016","article-title":"Slow ecosystem responses conditionally regulate annual carbon balance over 15 years in Californian oak-grass savanna","volume":"228\u2013229","author":"Ma","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.agrformet.2007.07.008","article-title":"Inter-annual variability in carbon dioxide exchange of an oak\/grass savanna and open grassland in California","volume":"147","author":"Ma","year":"2007","journal-title":"Agric. For. Meteorol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.agrformet.2019.01.017","article-title":"Assessing the carbon and climate benefit of restoring degraded agricultural peat soils to managed wetlands","volume":"268","author":"Hemes","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Ramachandran, B., Justice, C.O., and Abrams, M.J. (2011). MODIS-Derived Terrestrial Primary Production. Land Remote Sensing and Global Environmental Change: NASA\u2019s Earth Observing System and the Science of ASTER and MODIS, Springer.","DOI":"10.1007\/978-1-4419-6749-7"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.agrformet.2019.02.040","article-title":"Improvement of satellite-based estimation of gross primary production through optimi-zation of meteorological parameters and high resolution land cover information at regional scale over East Asia","volume":"271","author":"Park","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1016\/j.rse.2009.04.013","article-title":"Evaluation of Collections 4 and 5 of the MODIS Gross Primary Productivity product and algo-rithm improvement at a tropical savanna site in northern Australia","volume":"113","author":"Kanniah","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1016\/j.rse.2010.01.022","article-title":"Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data","volume":"114","author":"Yuan","year":"2010","journal-title":"Remote. Sens. Environ."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"399","DOI":"10.2307\/1941899","article-title":"Potential Net Primary Productivity in South America: Application of a Global Model","volume":"1","author":"Raich","year":"1991","journal-title":"Ecol. Appl."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/2009EI275.1","article-title":"Twentieth-Century Droughts and Their Impacts on Terrestrial Carbon Cycling in China","volume":"13","author":"Xiao","year":"2009","journal-title":"Earth Interact."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Gitelson, A.A., Vi\u00f1a, A., Verma, S.B., Rundquist, D.C., Arkebauer, T.J., Keydan, G., Leavitt, B., Ciganda, V., Burba, G.G., and Suyker, A.E. (2006). Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity. J. Geophys. Res. Space Phys., 111.","DOI":"10.1029\/2005JD006017"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhou, D., Fan, J., Guo, Q., Chen, S., Wang, R., and Li, Y. (2019). Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Tempera-ture-Limited Grassland Ecosystems. Remote Sens., 11.","DOI":"10.3390\/rs11111333"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.rse.2013.03.033","article-title":"Phenology and gross primary production of two dominant savanna woodland ecosystems in Southern Africa","volume":"135","author":"Jin","year":"2013","journal-title":"Remote. Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2012.12.023","article-title":"Evaluation of MODIS gross primary productivity for Africa using eddy covariance data","volume":"131","author":"Zhao","year":"2013","journal-title":"Remote. Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Lin, S., Li, J., Liu, Q., Huete, A., and Li, L. (2018). Effects of Forest Canopy Vertical Stratification on the Estimation of Gross Primary Production by Remote Sensing. Remote. Sens., 10.","DOI":"10.3390\/rs10091329"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/j.agrformet.2015.09.005","article-title":"Improving the performance of remote sensing models for capturing intra- and inter-annual varia-tions in daily GPP: An analysis using global FLUXNET tower data","volume":"214\u2013215","author":"Verma","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.rse.2005.10.009","article-title":"Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions","volume":"100","author":"Gebremichael","year":"2006","journal-title":"Remote. Sens. Environ."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.ecolind.2016.08.022","article-title":"Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of mul-tiple land cover types","volume":"72","author":"Shi","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.rse.2016.08.030","article-title":"Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS)","volume":"186","author":"Jiang","year":"2016","journal-title":"Remote. Sens. Environ."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.agrformet.2014.11.004","article-title":"Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States","volume":"201","author":"Xin","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1514","DOI":"10.1016\/j.agrformet.2011.06.007","article-title":"Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data","volume":"151","author":"Kalfas","year":"2011","journal-title":"Agric. For. Meteorol."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.agrformet.2015.03.016","article-title":"Uncertainty in simulating gross primary production of cropland ecosystem from satellite-based mod-els","volume":"207","author":"Yuan","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.5194\/bg-11-2185-2014","article-title":"Remote sensing of annual terrestrial gross primary productivity from MODIS: An assessment using the FLUXNET La Thuile data set","volume":"11","author":"Verma","year":"2014","journal-title":"Biogeosciences"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"63","DOI":"10.2307\/1929923","article-title":"Seasonal Variations of the Photosynthetic Efficiency of Evergreen Conifers","volume":"40","author":"Bourdeau","year":"1959","journal-title":"Ecology"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1111\/j.1469-8137.1977.tb02202.x","article-title":"Changes in Chlorophyll And Carotenoid Content, Specific Leaf Area and Dry Weight Fraction in Sitka Spruce, In Response To Shading And Season","volume":"79","author":"Lewandowska","year":"1977","journal-title":"New Phytol."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1023\/A:1006645632023","article-title":"Effects of shade on morphology, chlorophyll concentration, and chlorophyll fluorescence of four Pacific Northwest conifer species","volume":"19","author":"Khan","year":"2000","journal-title":"New For."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1029\/2006JG000162","article-title":"On the use of MODIS EVI to assess gross primary productivity of North American ecosystems","volume":"111","author":"Sims","year":"2006","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1016\/j.rse.2011.02.024","article-title":"Parameterization of a diagnostic carbon cycle model for continental scale ap-plication","volume":"115","author":"King","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1016\/j.agrformet.2008.12.007","article-title":"Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices","volume":"149","author":"Wu","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.ecoinf.2007.03.009","article-title":"Discriminating and mapping the C3 and C4 composition of grasslands in the northern Great Plains, USA","volume":"2","author":"Foody","year":"2007","journal-title":"Ecol. Inform."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2017.10.046","article-title":"Spatio-temporal fusion for daily Sentinel-2 images","volume":"204","author":"Wang","year":"2018","journal-title":"Remote. Sens. Environ."},{"key":"ref_99","unstructured":"Korosov, A., and Pozdnyakov, D. (2011, January 13\u201317). Fusion of data from Sentinel-2\/MSI and Sentinel-3\/OLCI. Proceedings of the Living Planet Symposium, Milan, Italy."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/978-3-642-80913-2_4","article-title":"Methods of Assessing Terrestrial Productivty","volume":"14","author":"Whittaker","year":"1975","journal-title":"Primary Productivity of the Biosphere"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1080\/01431160304984","article-title":"Forest ecosystem chlorophyll content: Implications for remotely sensed estimates of net primary productivity","volume":"24","author":"Dawson","year":"2003","journal-title":"Int. J. Remote. Sens."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"1290","DOI":"10.1109\/TGRS.2017.2754221","article-title":"Design of a Generic 3-D Scene Generator for Passive Optical Missions and Its Implementation for the ESA\u2019s FLEX\/Sentinel-3 Tandem Mission","volume":"56","author":"Tenjo","year":"2017","journal-title":"IEEE Trans. Geosci. Remote. Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/1015\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:34:49Z","timestamp":1760160889000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/1015"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,8]]},"references-count":102,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["rs13051015"],"URL":"https:\/\/doi.org\/10.3390\/rs13051015","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,8]]}}}