{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T17:14:36Z","timestamp":1767892476828,"version":"3.49.0"},"reference-count":79,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,6,3]],"date-time":"2019-06-03T00:00:00Z","timestamp":1559520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFA0606001,2017YFA0604301 & 2017YFA0604302"],"award-info":[{"award-number":["2018YFA0606001,2017YFA0604301 & 2017YFA0604302"]}]},{"name":"State Key Laboratory of Resources and Environment Information System","award":["O88RA901YA"],"award-info":[{"award-number":["O88RA901YA"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771114 & 41271116"],"award-info":[{"award-number":["41771114 & 41271116"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global retrieval of solar-induced chlorophyll fluorescence (SIF) using remote sensing by means of satellites has been developed rapidly in recent years. Exploring how SIF could improve the characterization of photosynthesis and its role in the land surface carbon cycle has gradually become a very important and active area. However, compared with other gross primary production (GPP) models, the robustness of the parameterization of the SIF model under different circumstances has rarely been investigated. In this study, we examined and compared the effects of temporal aggregation and meteorological conditions on the stability of model parameters for the SIF model ( \u03b5 \/ S I F yield ), the one-leaf light-use efficiency (SL-LUE) model ( \u03b5 max ), and the two-leaf LUE (TL-LUE) model ( \u03b5 msu and \u03b5 msh ). The three models were parameterized based on a maize\u2013wheat rotation eddy-covariance flux tower data in Yucheng, Shandong Province, China by using the Metropolis\u2013Hasting algorithm. The results showed that the values of the \u03b5 \/ S I F yield and \u03b5 max were similarly robust and considerably more stable than \u03b5 msu and \u03b5 msh for all temporal aggregation levels. Under different meteorological conditions, all the parameters showed a certain degree of fluctuation and were most affected at the mid-day scale, followed by the monthly scale and finally at the daily scale. Nonetheless, the averaged coefficient of variation ( C V ) of \u03b5 \/ S I F yield was relatively small (15.0%) and was obviously lower than \u03b5 max ( C V = 27.0%), \u03b5 msu ( C V = 43.2%), and \u03b5 msh ( C V = 53.1%). Furthermore, the SIF model\u2019s performance for estimating GPP was better than that of the SL-LUE model and was comparable to that of the TL-LUE model. This study indicates that, compared with the LUE-based models, the SIF-based model without climate-dependence is a good predictor of GPP and its parameter is more likely to converge for different temporal aggregation levels and under varying environmental restrictions in croplands. We suggest that more flux tower data should be used for further validation of parameter convergence in other vegetation types.<\/jats:p>","DOI":"10.3390\/rs11111328","type":"journal-article","created":{"date-parts":[[2019,6,3]],"date-time":"2019-06-03T11:31:01Z","timestamp":1559561461000},"page":"1328","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Effects of the Temporal Aggregation and Meteorological Conditions on the Parameter Robustness of OCO-2 SIF-Based and LUE-Based GPP Models for Croplands"],"prefix":"10.3390","volume":"11","author":[{"given":"Xiaofeng","family":"Lin","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China"}]},{"given":"Baozhang","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China"}]},{"given":"Huifang","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Meteorological Information Center of Beijing, Beijing Meteorological Bureau, No. 44, Zizhuyuan Road, Haidian District, Beijing 100089, China"}]},{"given":"Lifeng","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China"}]},{"given":"Yawen","family":"Kong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1016\/j.rse.2017.09.034","article-title":"Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests","volume":"204","author":"Li","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_2","unstructured":"Odum, E.P., Barrett, G.W., and Lu, J.J. (1971). Fundamentals of Ecology, Saunders."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1002\/2016JG003580","article-title":"Effect of meteorological conditions on the relationship between solar-induced fluorescence and gross primary productivity at an OzFlux grassland site","volume":"122","author":"Verma","year":"2017","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Cui, T., Sun, R., Qiao, C., Zhang, Q., Yu, T., Liu, G., and Liu, Z. (2017). Estimating Diurnal Courses of Gross Primary Production for Maize: A Comparison of Sun-Induced Chlorophyll Fluorescence, Light-Use Efficiency and Process-Based Models. Remote Sens., 9.","DOI":"10.3390\/rs9121267"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.agrformet.2016.12.019","article-title":"Seasonal fluctuations of photosynthetic parameters for light use efficiency models and the impacts on gross primary production estimation","volume":"236","author":"Lin","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_6","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 vegetation in North America","volume":"183","author":"Zhang","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"L17706","DOI":"10.1029\/2011GL048738","article-title":"New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity","volume":"38","author":"Frankenberg","year":"2011","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2014.02.007","article-title":"Prospects for chlorophyll fluorescence remote sensing from the orbiting carbon observatory-2","volume":"147","author":"Frankenberg","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2589","DOI":"10.5194\/amt-8-2589-2015","article-title":"A linear method for the retrieval of sun-induced chlorophyll fluorescence from GOME-2 and SCIAMACHY data","volume":"8","author":"Guanter","year":"2015","journal-title":"Atmos. Meas. Tech."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"eaam5747","DOI":"10.1126\/science.aam5747","article-title":"OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence","volume":"358","author":"Sun","year":"2017","journal-title":"Science"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1016\/j.rse.2018.02.016","article-title":"Overview of Solar-Induced chlorophyll Fluorescence (SIF) from the Orbiting Carbon Observatory-2: Retrieval, cross-mission comparison, and global monitoring for GPP","volume":"209","author":"Sun","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"637","DOI":"10.5194\/bg-8-637-2011","article-title":"First observations of global and seasonal terrestrial chlorophyll fluorescence from space","volume":"8","author":"Joiner","year":"2011","journal-title":"Biogeosciences"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.rse.2012.02.006","article-title":"Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements","volume":"121","author":"Guanter","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"809","DOI":"10.5194\/amt-5-809-2012","article-title":"Filling-in of near-infrared solar lines by terrestrial fluorescence and other geophysical effects: Simulations and space-based observations from SCIAMACHY and GOSAT","volume":"5","author":"Joiner","year":"2012","journal-title":"Atmos. Meas. Tech."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2803","DOI":"10.5194\/amt-6-2803-2013","article-title":"Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: Methodology, simulations, and application to GOME-2","volume":"6","author":"Joiner","year":"2013","journal-title":"Atmos. Meas. Tech."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sanders, A., Verstraeten, W., Kooreman, M., Van Leth, T., Beringer, J., and Joiner, J. (2016). Spaceborne sun-induced vegetation fluorescence time series from 2007 to 2015 evaluated with Australian flux tower measurements. Remote Sens., 8.","DOI":"10.3390\/rs8110895"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3939","DOI":"10.5194\/amt-9-3939-2016","article-title":"New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: Simulations and application to GOME-2 and SCIAMACHY","volume":"9","author":"Joiner","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.rse.2015.05.018","article-title":"Global retrieval of marine and terrestrial chlorophyll fluorescence at its red peak using hyperspectral top of atmosphere radiance measurements: Feasibility study and first results","volume":"166","author":"Wolanin","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.rse.2016.11.021","article-title":"Application of satellite solar-induced chlorophyll fluorescence to understanding large-scale variations in vegetation phenology and function over northern high latitude forests","volume":"190","author":"Jeong","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1002\/2016GL070842","article-title":"Tundra photosynthesis captured by satellite-observed solar-induced chlorophyll fluorescence","volume":"44","author":"Luus","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"E1327","DOI":"10.1073\/pnas.1320008111","article-title":"Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence","volume":"111","author":"Guanter","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1111\/gcb.13136","article-title":"Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence","volume":"22","author":"Guan","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"20130171","DOI":"10.1098\/rspb.2013.0171","article-title":"Forest productivity and water stress in Amazonia: Observations from GOSAT chlorophyll fluorescence","volume":"280","author":"Lee","year":"2013","journal-title":"Proc. R. Soc. B Biol. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1038\/ngeo2382","article-title":"Photosynthetic seasonality of global tropical forests constrained by hydroclimate","volume":"8","author":"Guan","year":"2015","journal-title":"Nat. Geosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2108","DOI":"10.3390\/rs6032108","article-title":"Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, andMODIS in Southeast Asia","volume":"6","author":"Wang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_26","unstructured":"Hongji, Z., Aiwen, L., Lunche, W., Yu, X., and Ling, Z. (2016). Evaluation of modis gross primary production across multiple biomes in china using eddy covariance flux data. Remote Sens., 8."},{"key":"ref_27","unstructured":"Lunche, W., Hongji, Z., Aiwen, L., Ling, Z., Wenmin, Q., and Qiyong, D. (2017). Evaluation of the latest modis gpp products across multiple biomes using global eddy covariance flux data. Remote Sens., 9."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.agrformet.2013.01.003","article-title":"Development of a two-leaf light use efficiency model for improving the calculation of terrestrial gross primary productivity","volume":"173","author":"He","year":"2013","journal-title":"Agric. For. Meteorol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"G03010","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. Biogeosci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1002\/2014JG002876","article-title":"Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites","volume":"121","author":"Zhou","year":"2016","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3857","DOI":"10.3390\/rs4123857","article-title":"Estimating the maximal light use efficiency for different vegetation through the CASA Model combined with time-series remote sensing data and ground measurements","volume":"4","author":"Li","year":"2012","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3321","DOI":"10.3390\/rs6043321","article-title":"Evaluating Parameter Adjustment in the MODIS Gross Primary Production Algorithm Based on Eddy Covariance Tower Measurements","volume":"6","author":"Chen","year":"2014","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1111\/nph.15176","article-title":"Must we incorporate soil moisture information when applying light use efficiency models with satellite remote sensing information?","volume":"218","author":"Baldocchi","year":"2018","journal-title":"New Phytol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Muramatsu, K., Furumi, S., Soyama, N., and Daigo, M. (2014, January 8). Estimating the seasonal maximum light use efficiency. Proceedings of the SPIE Asia-Pacific Remote Sensing, Beijing, China.","DOI":"10.1117\/12.2069142"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.rse.2015.06.004","article-title":"Far-red sun-induced chlorophyll fluorescence shows ecosystem-specific relationships to gross primary production: An assessment based on observational and modeling approaches","volume":"166","author":"Damm","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2874","DOI":"10.1111\/gcb.13590","article-title":"Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest","volume":"23","author":"Yang","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1002\/2016GL070775","article-title":"Multiscale analyses of solar-induced florescence and gross primary production","volume":"44","author":"Wood","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3508","DOI":"10.1029\/2017GL076354","article-title":"Spatio-Temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll","volume":"45","author":"Zhang","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"G02014","DOI":"10.1029\/2010JG001593","article-title":"Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from fluxnet data","volume":"116","author":"Bonan","year":"2011","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1007\/s00382-010-0741-2","article-title":"Sensitivity of simulated terrestrial carbon assimilation and canopy transpiration to different stomatal conductance and carbon assimilation schemes","volume":"36","author":"Chen","year":"2010","journal-title":"Clim. Dyn."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4509","DOI":"10.5194\/bg-12-4509-2015","article-title":"Reviews and syntheses: Optical sampling of the flux tower footprint","volume":"12","author":"Gamon","year":"2015","journal-title":"Biogeosciences"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.ecolind.2018.01.028","article-title":"Uncertainty in simulating regional gross primary productivity from satellite-based models over northern China grassland","volume":"88","author":"Jia","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.rse.2006.04.006","article-title":"A mobile tram system for systematic sampling of ecosystem optical properties","volume":"103","author":"Gamon","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1890\/15-1434","article-title":"Comparison of solar-induced chlorophyll fluorescence, light-use efficiency, and process-based GPP models in maize","volume":"26","author":"Wagle","year":"2016","journal-title":"Ecol. Appl."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.compag.2007.01.003","article-title":"Instrumentation and approach for unattended year round tower based measurements of spectral reflectance","volume":"56","author":"Hilker","year":"2007","journal-title":"Comput. Electron. Agric."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"21077","DOI":"10.1029\/95JD02371","article-title":"On the derivation of kernels for kernel driven models of bidirectional reflectance","volume":"100","author":"Wanner","year":"1995","journal-title":"J. Geophys. Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1109\/36.841980","article-title":"An algorithm for the retrieval of albedo from space using semiempirical BRDF models","volume":"38","author":"Lucht","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","unstructured":"Maier, S.W., G\u00fcnther, K.P., and Stellmes, M. (2003). Sun-induced fluorescence: A new tool for precision farming. Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology, The American Society of Agronomy."},{"key":"ref_49","first-page":"2451","article-title":"Extraction and analysis of Solar\u2014induced chlorophyl fluorescence of wheat with ground-based hyperspectral imaging system","volume":"33","author":"Wang","year":"2013","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1117\/12.7971842","article-title":"The MK II Fraunhofer Line Discriminator (FLD-II) for Airborne and Orbital Remote Sensing of Solar-Stimulated Luminescence","volume":"14","author":"Plascyk","year":"1975","journal-title":"Opt. Eng."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1109\/LGRS.2008.2001180","article-title":"Improved Fraunhofer Line Discrimination Method for Vegetation Fluorescence Quantification","volume":"5","author":"Alonso","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1882","DOI":"10.1016\/j.rse.2011.03.011","article-title":"Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence","volume":"115","author":"Damm","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"10656","DOI":"10.3390\/rs61110656","article-title":"Assessing band sensitivity to atmospheric radiation transfer for space-based retrieval of solar-induced chlorophyll fluorescence","volume":"6","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"10626","DOI":"10.3390\/rs70810626","article-title":"New spectral fitting method for full-spectrum solar-induced chlorophyll fluorescence retrieval based on principal components analysis","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agrformet.2016.06.014","article-title":"Directly estimating diurnal changes in GPP for C3 and C4 crops using far-red sun-induced chlorophyll fluorescence","volume":"232","author":"Liu","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relation between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1080\/01431169308953986","article-title":"Red edge spectral measurements from sugar maple leaves","volume":"14","author":"Vogelmann","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2230","DOI":"10.1109\/TGRS.2006.872089","article-title":"Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter","volume":"44","author":"Chen","year":"2006","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_59","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_60","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.isprsjprs.2012.01.003","article-title":"Effect of canopy structure on sun-induced chlorophyll fluorescence","volume":"68","author":"Fournier","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0304-3800(99)00156-8","article-title":"Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications","volume":"124","author":"Chen","year":"1999","journal-title":"Ecol. Model."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1016\/j.jenvman.2006.08.018","article-title":"LAI inversion algorithm based on directional reflectance kernels","volume":"85","author":"Tang","year":"2007","journal-title":"J. Environ. Manag."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2953","DOI":"10.1016\/j.csda.2005.05.007","article-title":"Confidence interval for a coefficient of quartile variation","volume":"50","author":"Bonett","year":"2006","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"8995","DOI":"10.1029\/JC090iC05p08995","article-title":"Statistics for the evaluation and comparison of models","volume":"90","author":"Willmott","year":"1985","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3354\/cr030079","article-title":"Advantages of the mean absolute error (mae) over the root mean square error (rmse) in assessing average model performance","volume":"30","author":"Willmott","year":"2005","journal-title":"Clim. Res."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"2977","DOI":"10.1002\/2015GL063201","article-title":"Solar-induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest","volume":"42","author":"Yang","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"3469","DOI":"10.1111\/gcb.12948","article-title":"Simulations of chlorophyll fluorescence incorporated into the C ommunity L and M odel version 4","volume":"21","author":"Lee","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2014.06.022","article-title":"The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange","volume":"152","author":"Joiner","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_69","unstructured":"Norman, J.M., and Arkebauer, T.J. (1991). Predicting canopy light-use efficiency from leaf characteristics. Modeling Plant and Soil Systems, The American Society of Agronomy."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1016\/j.rse.2009.02.001","article-title":"Tracking seasonal drought effects on ecosystem light use efficiency with satellite-based PRI in a Mediterranean forest","volume":"113","author":"Goerner","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"3064","DOI":"10.1016\/j.rse.2008.03.002","article-title":"Regional mapping of gross light-use efficiency using MODIS spectral indices","volume":"112","author":"Drolet","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Boland, J., and Ridley, B. (2008). Models of Diffuse Solar Fraction. Modeling Solar Radiation at the Earth\u2019s Surface, Springer.","DOI":"10.1007\/978-3-540-77455-6_8"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1071\/PP9950209","article-title":"Assessment of photosystem II photochemical quantum yield by chlorophyll fluorescence quenching analysis","volume":"22","author":"Schreiber","year":"1995","journal-title":"Funct. Plant Biol."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/0005-2728(87)90190-3","article-title":"Quantum efficiency of photosystem II in relation to \u2018energy\u2019-dependent quenching of chlorophyll fluorescence","volume":"894","author":"Weis","year":"1987","journal-title":"BBA Bioenerg."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1093\/jexbot\/51.345.659","article-title":"Chlorophyll fluorescence\u2014A practical guide","volume":"51","author":"Maxwell","year":"2000","journal-title":"J. Exp. Bot."},{"key":"ref_76","unstructured":"Mohammed, G.H., Goulas, Y., Magnani, F., Moreno, J., Olejn\u00ed\u010dkov\u00e1, J., Rascher, U., van der Tol, C., Verhoef, W., A\u010d, A., and Daumard, F. (2014). 2012 FLEX\/Sentinel-3 Tandem Mission Photosynthesis Study, P & M Technologies. Final Report. ESTEC contract no. 4000106396\/12\/NL\/AF."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Guanter, L., Berry, J.A., van der Tol, C., and Joiner, J. (2016, January 10\u201315). Can we retrieve vegetation photosynthetic capacity paramter from solar-induced fluorescence?. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729437"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"4067","DOI":"10.5194\/bg-12-4067-2015","article-title":"Investigating the usefulness of satellite-derived fluorescence data in inferring gross primary productivity within the carbon cycle data assimilation system","volume":"12","author":"Koffi","year":"2015","journal-title":"Biogeosciences"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1973","DOI":"10.1038\/s41598-018-20024-w","article-title":"Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data","volume":"8","author":"MacBean","year":"2018","journal-title":"Sci. Rep."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/11\/1328\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:55:42Z","timestamp":1760187342000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/11\/1328"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,3]]},"references-count":79,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,6]]}},"alternative-id":["rs11111328"],"URL":"https:\/\/doi.org\/10.3390\/rs11111328","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,3]]}}}