{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T09:27:04Z","timestamp":1772962024956,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T00:00:00Z","timestamp":1679356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Space Agency","award":["4000118570\/16\/I-NB"],"award-info":[{"award-number":["4000118570\/16\/I-NB"]}]},{"name":"European Space Agency","award":["S3-4SCI LAND"],"award-info":[{"award-number":["S3-4SCI LAND"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>(1) Land surface models require inputs of temperature and moisture variables to generate predictions of gross primary production (GPP). Differences between leaf and air temperature vary temporally and spatially and may be especially pronounced under conditions of low soil moisture availability. The Sentinel-3 satellite mission offers estimates of the land surface temperature (LST), which for vegetated pixels can be adopted as the canopy temperature. Could remotely sensed estimates of LST offer a parsimonious input to models by combining information on leaf temperature and hydration? (2) Using a light use efficiency model that requires only a handful of input variables, we generated GPP simulations for comparison with eddy-covariance inferred estimates available from flux sites within the Integrated Carbon Observation System. Remotely sensed LST and greenness data were input from Sentinel-3. Gridded air temperature data were obtained from the European Centre for Medium-Range Weather Forecasts. We chose the years 2018\u20132019 to exploit the natural experiment of a pronounced European drought. (3) Simulated GPP showed good agreement with flux-derived estimates. During dry conditions, simulations forced with LST performed better than those with air temperature for shrubland, grassland and savanna sites. (4) This study advances the prospect for a global GPP monitoring system that will rely primarily on remotely sensed inputs.<\/jats:p>","DOI":"10.3390\/rs15061693","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T06:00:01Z","timestamp":1679464801000},"page":"1693","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Towards a General Monitoring System for Terrestrial Primary Production: A Test Spanning the European Drought of 2018"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6492-4507","authenticated-orcid":false,"given":"Keith J.","family":"Bloomfield","sequence":"first","affiliation":[{"name":"Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roel","family":"van Hoolst","sequence":"additional","affiliation":[{"name":"Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7888-1501","authenticated-orcid":false,"given":"Manuela","family":"Balzarolo","sequence":"additional","affiliation":[{"name":"Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5705-1787","authenticated-orcid":false,"given":"Ivan A.","family":"Janssens","sequence":"additional","affiliation":[{"name":"Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9812-5837","authenticated-orcid":false,"given":"Sara","family":"Vicca","sequence":"additional","affiliation":[{"name":"Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9810-3790","authenticated-orcid":false,"given":"Darren","family":"Ghent","sequence":"additional","affiliation":[{"name":"National Centre for Earth Observation (NCE), Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1296-6764","authenticated-orcid":false,"given":"I. Colin","family":"Prentice","sequence":"additional","affiliation":[{"name":"Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK"},{"name":"Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,21]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1175\/JCLI-D-12-00579.1","article-title":"Uncertainties in CMIP5 Climate Projections due to Carbon Cycle Feedbacks","volume":"27","author":"Friedlingstein","year":"2014","journal-title":"J. Clim."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1111\/gcb.14807","article-title":"How eddy covariance flux measurements have contributed to our understanding of Global Change Biology","volume":"26","author":"Baldocchi","year":"2020","journal-title":"Glob. Chang. Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1038\/s41597-020-0534-3","article-title":"The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data","volume":"7","author":"Pastorello","year":"2020","journal-title":"Sci. Data"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1046\/j.1365-2486.2003.00629.x","article-title":"Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: Past, present and future","volume":"9","author":"Baldocchi","year":"2003","journal-title":"Glob. Chang. Biol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"108350","DOI":"10.1016\/j.agrformet.2021.108350","article-title":"Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites","volume":"301","author":"Chu","year":"2021","journal-title":"Agric. For. Meteorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1007\/BF00386231","article-title":"A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species","volume":"149","author":"Farquhar","year":"1980","journal-title":"Planta"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1093\/treephys\/18.3.167","article-title":"Physiological basis of the light use efficiency model","volume":"18","author":"Medlyn","year":"1998","journal-title":"Tree Physiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1046\/j.1365-3040.1998.00311.x","article-title":"A mechanistic analysis of light and carbon use efficiencies","volume":"21","author":"Dewar","year":"1998","journal-title":"Plant Cell Environ."},{"key":"ref_10","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_11","first-page":"277","article-title":"Climate and the efficiency of crop production in Britain","volume":"281","author":"Monteith","year":"1977","journal-title":"Philos. Trans. R. Soc. B"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wang, X., and Ren, J. (2021). Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models. Land, 10.","DOI":"10.3390\/land10030329"},{"key":"ref_13","first-page":"5987","article-title":"Reliable, robust and realistic: The three R\u2019s of next-generation land-surface modelling","volume":"15","author":"Prentice","year":"2015","journal-title":"Atmospheric Meas. Tech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1038\/s41477-017-0006-8","article-title":"Towards a universal model for carbon dioxide uptake by plants","volume":"3","author":"Wang","year":"2017","journal-title":"Nat. Plants"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.5194\/gmd-13-1545-2020","article-title":"P-model v1.0: An optimality-based light use efficiency model for simulating ecosystem gross primary production","volume":"13","author":"Stocker","year":"2020","journal-title":"Geosci. Model Dev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"124050","DOI":"10.1088\/1748-9326\/abc64e","article-title":"Recent trends in gross primary production and their drivers: Analysis and modelling at flux-site and global scales","volume":"15","author":"Cai","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1046\/j.0016-8025.2003.01050.x","article-title":"In vivo temperature response functions of parameters required to model RuBP-limited photosynthesis","volume":"26","author":"Bernacchi","year":"2003","journal-title":"Plant Cell Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1111\/nph.14283","article-title":"A roadmap for improving the representation of photosynthesis in Earth system models","volume":"213","author":"Rogers","year":"2017","journal-title":"New Phytol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1111\/j.1365-3040.2001.00668.x","article-title":"Improved temperature response functions for models of Rubisco-limited photosynthesis","volume":"24","author":"Bernacchi","year":"2001","journal-title":"Plant Cell Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1146\/annurev.pp.31.060180.002423","article-title":"Photosynthetic Response and Adaptation to Temperature in Higher Plants","volume":"31","author":"Berry","year":"1980","journal-title":"Annu. Rev. Plant Physiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1111\/nph.15668","article-title":"Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale","volume":"222","author":"Kumarathunge","year":"2019","journal-title":"New Phytol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1746","DOI":"10.1111\/nph.17321","article-title":"Imaging canopy temperature: Shedding (thermal) light on ecosystem processes","volume":"230","author":"Still","year":"2021","journal-title":"New Phytol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1111\/geb.12614","article-title":"Biophysical homoeostasis of leaf temperature: A neglected process for vegetation and land-surface modelling","volume":"26","author":"Dong","year":"2017","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1618","DOI":"10.1111\/pce.13208","article-title":"Differences in leaf thermoregulation and water use strategies between three co-occurring Atlantic forest tree species","volume":"41","author":"Fauset","year":"2018","journal-title":"Plant Cell Environ."},{"key":"ref_25","unstructured":"Jennings, D. (1977). Integration of Activity in Higher Plants, Cambridge University Press."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2134","DOI":"10.1111\/j.1365-2486.2010.02375.x","article-title":"Reconciling the optimal and empirical approaches to modelling stomatal conductance","volume":"17","author":"Medlyn","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.5194\/bg-17-1655-2020","article-title":"Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003","volume":"17","author":"Buras","year":"2020","journal-title":"Biogeosciences"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature03972","article-title":"Europe-wide reduction in primary productivity caused by the heat and drought in 2003","volume":"437","author":"Ciais","year":"2005","journal-title":"Nature"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2015.09.0131","article-title":"Modeling Soil Processes: Review, Key Challenges, and New Perspectives","volume":"15","author":"Vereecken","year":"2016","journal-title":"Vadose Zone J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1038\/s41467-022-28652-7","article-title":"Atmospheric dryness reduces photosynthesis along a large range of soil water deficits","volume":"13","author":"Fu","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"28269","DOI":"10.1038\/srep28269","article-title":"Remotely-sensed detection of effects of extreme droughts on gross primary production","volume":"6","author":"Vicca","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1430","DOI":"10.1111\/nph.15123","article-title":"Quantifying soil moisture impacts on light use efficiency across biomes","volume":"218","author":"Stocker","year":"2018","journal-title":"New Phytol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1016\/j.agrformet.2013.05.009","article-title":"How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress","volume":"182","author":"Zhou","year":"2013","journal-title":"Agric. For. Meteorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1038\/s41561-019-0318-6","article-title":"Drought impacts on terrestrial primary production underestimated by satellite monitoring","volume":"12","author":"Stocker","year":"2019","journal-title":"Nat. Geosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3193","DOI":"10.1111\/gcb.14747","article-title":"How ecologists define drought, and why we should do better","volume":"25","author":"Slette","year":"2019","journal-title":"Glob. Chang. Biol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1175\/2009JCLI2909.1","article-title":"A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index","volume":"23","year":"2010","journal-title":"J. Clim."},{"key":"ref_37","unstructured":"R Core Team (2020). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: http:\/\/www.R-project.org."},{"key":"ref_38","unstructured":"Stocker, B.D. (2023, February 15). rpmodel v1.0.4. Available online: https:\/\/zenodo.org\/record\/3560169#.ZBl05HZBxD8."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"939","DOI":"10.2134\/agronj1984.00021962007600060018x","article-title":"A Generalized Relationship between Photosynthetically Active Radiation and Solar Radiation","volume":"76","author":"Meek","year":"1984","journal-title":"Agron. J."},{"key":"ref_40","unstructured":"Allen, R., Pereira, L., Raes, D., and Smith, M. (1998). Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements, FAO. Available online: http:\/\/www.fao.org\/docrep\/x0490e\/x0490e00.htm."},{"key":"ref_41","unstructured":"Ghent, D., Dodd, E., Veal, K., Perry, M., Jimenez, C., and Ermida, S. (2023, February 15). CCI Land Surface Temperature Algorithm Theoretical Basis Document. LST-CCI-D2.2-ATBD. Available online: https:\/\/admin.climate.esa.int\/media\/documents\/LST-CCI-D2.2-ATBD_-_i3r0_-_Algorithm_Theoretical_Basis_Document.pdf."},{"key":"ref_42","first-page":"4409412","article-title":"On the Potential of Sentinel-2 for Estimating Gross Primary Production","volume":"60","author":"Migliavacca","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","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_44","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1111\/nph.16485","article-title":"Plant responses to rising vapor pressure deficit","volume":"226","author":"Grossiord","year":"2020","journal-title":"New Phytol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1111\/j.1365-2486.2009.02041.x","article-title":"Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: Critical issues and global evaluation","volume":"16","author":"Lasslop","year":"2010","journal-title":"Glob. Chang. Biol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2737","DOI":"10.1111\/j.1365-2486.2010.02171.x","article-title":"Characterization of ecosystem responses to climatic controls using artificial neural networks","volume":"16","author":"Moffat","year":"2010","journal-title":"Glob. Chang. Biol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1111\/gcb.16511","article-title":"Environmental controls on the light use efficiency of terrestrial gross primary production","volume":"29","author":"Bloomfield","year":"2023","journal-title":"Glob. Chang. Biol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"108347","DOI":"10.1016\/j.agrformet.2021.108347","article-title":"Only sun-lit leaves of the uppermost canopy exceed both air temperature and photosynthetic thermal optima in a wet tropical forest","volume":"301","author":"Miller","year":"2021","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Maleki, M., Arriga, N., Barrios, J.M., Wieneke, S., Liu, Q., Pe\u00f1uelas, J., Janssens, I.A., and Balzarolo, M. (2020). Estimation of Gross Primary Productivity (GPP) Phenology of a Short-Rotation Plantation Using Remotely Sensed Indices Derived from Sentinel-2 Images. Remote Sens., 12.","DOI":"10.3390\/rs12132104"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1111\/j.1365-2486.2006.01220.x","article-title":"Climatic controls on the carbon and water balances of a boreal aspen forest, 1994\u20132003","volume":"13","author":"Barr","year":"2007","journal-title":"Glob. Chang. Biol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Balzarolo, M., Pe\u00f1uelas, J., and Veroustraete, F. (2019). Influence of Landscape Heterogeneity and Spatial Resolution in Multi-Temporal In Situ and MODIS NDVI Data Proxies for Seasonal GPP Dynamics. Remote Sens., 11.","DOI":"10.3390\/rs11141656"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.3390\/rs70101154","article-title":"Soil Drought Anomalies in MODIS GPP of a Mediterranean Broadleaved Evergreen Forest","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1038\/nclimate3114","article-title":"The increasing importance of atmospheric demand for ecosystem water and carbon fluxes","volume":"6","author":"Novick","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_54","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 enhanced vegetation index and land surface temperature from MODIS","volume":"112","author":"Sims","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Guzinski, R., Nieto, H., Sandholt, I., and Karamitilios, G. (2020). Modelling High-Resolution Actual Evapotranspiration through Sentinel-2 and Sentinel-3 Data Fusion. Remote Sens., 12.","DOI":"10.3390\/rs12091433"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/6\/1693\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:59:50Z","timestamp":1760122790000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/6\/1693"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,21]]},"references-count":55,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["rs15061693"],"URL":"https:\/\/doi.org\/10.3390\/rs15061693","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,21]]}}}