{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:03:07Z","timestamp":1762956187940,"version":"build-2065373602"},"reference-count":83,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T00:00:00Z","timestamp":1567987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010560","name":"European Organization for the Exploitation of Meteorological Satellites","doi-asserted-by":"publisher","award":["LSA SAF CDOP-3"],"award-info":[{"award-number":["LSA SAF CDOP-3"]}],"id":[{"id":"10.13039\/501100010560","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI\/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI\/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.<\/jats:p>","DOI":"10.3390\/rs11182103","type":"journal-article","created":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T11:26:17Z","timestamp":1568028377000},"page":"2103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Climate Data Records of Vegetation Variables from Geostationary SEVIRI\/MSG Data: Products, Algorithms and Applications"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5888-0061","authenticated-orcid":false,"given":"Francisco Javier","family":"Garc\u00eda-Haro","sequence":"first","affiliation":[{"name":"Earth Physics and Thermodynamics Departmnet, Faculty of Physics, Universitat de Val\u00e8ncia, Dr. Moliner, 46100 Burjassot, Val\u00e8ncia, Spain"}]},{"given":"Fernando","family":"Camacho","sequence":"additional","affiliation":[{"name":"Earth Observation Laboratory (EOLAB), Parc Cient\u00edfic de la Universitat de Val\u00e8ncia, Catedr\u00e1tico Agust\u00edn Escardino, 9, 46980 Paterna, Val\u00e8ncia, Spain"}]},{"given":"Beatriz","family":"Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Earth Physics and Thermodynamics Departmnet, Faculty of Physics, Universitat de Val\u00e8ncia, Dr. Moliner, 46100 Burjassot, Val\u00e8ncia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5929-3942","authenticated-orcid":false,"given":"Manuel","family":"Campos-Taberner","sequence":"additional","affiliation":[{"name":"Earth Physics and Thermodynamics Departmnet, Faculty of Physics, Universitat de Val\u00e8ncia, Dr. Moliner, 46100 Burjassot, Val\u00e8ncia, Spain"}]},{"given":"Beatriz","family":"Fuster","sequence":"additional","affiliation":[{"name":"Earth Observation Laboratory (EOLAB), Parc Cient\u00edfic de la Universitat de Val\u00e8ncia, Catedr\u00e1tico Agust\u00edn Escardino, 9, 46980 Paterna, Val\u00e8ncia, Spain"}]},{"given":"Jorge","family":"S\u00e1nchez-Zapero","sequence":"additional","affiliation":[{"name":"Earth Observation Laboratory (EOLAB), Parc Cient\u00edfic de la Universitat de Val\u00e8ncia, Catedr\u00e1tico Agust\u00edn Escardino, 9, 46980 Paterna, Val\u00e8ncia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3548-1524","authenticated-orcid":false,"given":"Mar\u00eda Amparo","family":"Gilabert","sequence":"additional","affiliation":[{"name":"Earth Physics and Thermodynamics Departmnet, Faculty of Physics, Universitat de Val\u00e8ncia, Dr. Moliner, 46100 Burjassot, Val\u00e8ncia, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"ref_1","unstructured":"WMO (2011). A Global Framework for Climate Services-Empowering the Most Vulnerable, WMO."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1038\/nclimate1745","article-title":"The Global Framework for Climate Services","volume":"2","author":"Hewitt","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_3","unstructured":"Dowell, M., Lecomte, P., Husband, R., Schulz, J., Mohr, T., Tahara, Y., Eckman, R., Lindstrom, E., Wooldridge, C., and Hilding, S. (2019, June 01). Strategy Towards an Architecture for Climate Monitoring from Space. Available online: http:\/\/www.wmo.int\/pages\/prog\/sat\/documents\/ARCH_strategy-climate-architecture-space.pdf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2725","DOI":"10.1080\/01431161003743199","article-title":"The Satellite Application Facility for Land Surface Analysis","volume":"32","author":"Trigo","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1175\/BAMS-83-7-Schmetz-2","article-title":"An introduction to Meteosat Second Generation (MSG)","volume":"83","author":"Schmetz","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_6","unstructured":"Liang, S. (2017). Comprehensive Remote Sensing, Elsevier."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7393","DOI":"10.1029\/95JD02417","article-title":"Sensitivity of a general circulation model to global changes in leaf area index","volume":"101","author":"Chase","year":"1996","journal-title":"J. Geophys. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3536","DOI":"10.1175\/1520-0442(2001)014<3536:EOTUOS>2.0.CO;2","article-title":"Evaluation of the utility of satellite-based leaf area index data for climate simulation","volume":"14","author":"Buermann","year":"2001","journal-title":"J. Clim."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Leuning, R., Zhang, Y.Q., Rajaud, A., Cleugh, H., and Tu, K. (2008). A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman\u2013Monteith equation. Water Resour. Res., 44.","DOI":"10.1029\/2007WR006562"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.agsy.2018.05.007","article-title":"A high resolution, integrated system for rice yield forecast at district level","volume":"168","author":"Pagani","year":"2018","journal-title":"Agric. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.eja.2018.12.003","article-title":"Downscaling rice yield simulation at sub-field scale using remotely sensed LAI data","volume":"103","author":"Gilardelli","year":"2018","journal-title":"Eur. J. Agron."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.agrformet.2015.02.021","article-title":"Towards regional grain yield forecasting with 1-km resolution EO biophysical products: Strengths and limitation at pan-European level","volume":"206","author":"Duveiller","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1175\/1525-7541(2004)005<0823:TEOOFV>2.0.CO;2","article-title":"The effects of observed fractional vegetation cover on the land surface climatology of the community land model","volume":"5","author":"Barlage","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1175\/BAMS-D-13-00047.1","article-title":"The concept of essential climate variables in support of climate research, applications, and policy","volume":"95","author":"Bojinski","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","unstructured":"CTOS (2010). Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC (2010 Update), CTOS. Available online: https:\/\/library.wmo.int\/doc_num.php?explnum_id=3851."},{"key":"ref_16","unstructured":"GCOS-200 (2016). The Global Observing System for Climate: Implementation Needs, GCOS. Available online: https:\/\/library.wmo.int\/doc_num.php?explnum_id=3417."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"ACL6:1","DOI":"10.1029\/2001JD000751","article-title":"Global mapping of vegetation parameters from POLDER multiangular measurements for studies of surface-atmosphere interactions: A pragmatic method and validation","volume":"107","author":"Roujean","year":"2002","journal-title":"J. Geophys. Res."},{"key":"ref_18","unstructured":"Knyazikhin, Y., Glassy, J., Privette, J.L., Tian, Y., Lotsch, A., Zhang, Y., Wang, Y., Morisette, J.T., Votava, P., and Myneni, R.B. (1999). MODIS Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation Absorbed by Vegetation (FPAR) Product (MOD15) Algorithm Theoretical Basis Document, NASA Goddard Space Flight Center."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.rse.2003.05.002","article-title":"Performance of the MISR LAI and FPAR algorithm: A case study in Africa","volume":"88","author":"Hu","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1080\/014311699212542","article-title":"The MERIS Global Vegetation Index (MGVI): Description and preliminary application","volume":"20","author":"Gobron","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.rse.2006.07.014","article-title":"Neural network estimation of LAI, fAPAR, fCover and LAI\u00d7Cab, from top of canopy MERIS reflectance data: Principles and validation","volume":"105","author":"Bacour","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_22","first-page":"5","article-title":"A Global Vegetation Index for SeaWiFS: Design and Applications","volume":"Volume 7","author":"Beniston","year":"2001","journal-title":"Remote Sensing and Climate Modeling: Synergies and Limitations SE-1"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2007.02.018","article-title":"LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm","volume":"110","author":"Baret","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.rse.2012.12.027","article-title":"GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production","volume":"137","author":"Baret","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.isprsjprs.2018.03.005","article-title":"Derivation of global vegetation biophysical parameters from EUMETSAT Polar System","volume":"139","author":"Laparra","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1078\/0176-1617-01176","article-title":"Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation","volume":"161","author":"Gitelson","year":"2004","journal-title":"J. Plant Physiol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Widlowski, J.L., Taberner, M., Pinty, B., Bruniquel-Pinel, V., Disney, M., Fernandes, R., Gastellu-Etchegorry, J.P., Gobron, N., Kuusk, A., and Lavergne, T. (2007). Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models. J. Geophys. Res. Atmos., 112.","DOI":"10.1029\/2006JD007821"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1051\/agro:2000105","article-title":"Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data","volume":"20","author":"Weiss","year":"2000","journal-title":"Agronomie"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1016\/j.rse.2008.01.026","article-title":"PROSPECT + SAIL models: A review of use for vegetation characterization","volume":"113","author":"Jacquemoud","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.rse.2005.10.022","article-title":"Green leaf phenology at Landsat resolution: Scaling from the field to the satellite","volume":"100","author":"Fisher","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Filipponi, F., Valentini, E., Nguyen Xuan, A., Guerra, C.A., Wolf, F., Andrzejak, M., and Taramelli, A. (2018). Global MODIS Fraction of Green Vegetation Cover for Monitoring Abrupt and Gradual Vegetation Changes. Remote Sens., 10.","DOI":"10.3390\/rs10040653"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR absorbed by vegetation from bidirectional reflectance measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3841","DOI":"10.1109\/TGRS.2008.2001798","article-title":"Land surface albedo derived on a daily basis from Meteosat second generation observations","volume":"46","author":"Geiger","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","unstructured":"Geiger, B., Carrer, D., Hautecoeur, O., Franchist\u00e9guy, L., Roujean, J.-L., Catherine Meurey, X.C., Jacob, G., and Algorithm Theoretical Basis Document (ATBD) (2019, July 12). Land Surface Albedo PRODUCTS: LSA-103 (ETAL). Available online: Ref: SAF\/LAND\/MF\/ATBD_ETAL\/1.3, 25 November 2016, 41 pp."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: A new approach to global land cover mapping from earth observation data","volume":"26","author":"Bartholome","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Bishop, C.M. (1995). Neural Networks for Pattern Recognition, Oxford University Press.","DOI":"10.1093\/oso\/9780198538493.001.0001"},{"key":"ref_37","unstructured":"McLachlan, G.J., and Krishnan, T. (1997). The EM Algorithm and Extensions, Wiley."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1111\/j.2517-6161.1979.tb01084.x","article-title":"Comments on model selection criteria of Akaike and Schwartz","volume":"41","author":"Stone","year":"1979","journal-title":"J. R. Stat. Soc."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1198\/016214502760047131","article-title":"Model-Based Clustering, Discriminant Analysis, and Density Estimation","volume":"97","author":"Fraley","year":"2002","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2135","DOI":"10.1080\/01431160512331337817","article-title":"A new tool for variable multiple endmember spectral mixture analysis (VMESMA)","volume":"26","author":"Sommer","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0034-4257(98)00037-6","article-title":"Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models","volume":"65","author":"Roberts","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1109\/36.841987","article-title":"Endmember Bundles: A New Approach to Incorporating Endmember Variability into Spectral Mixture Analysis","volume":"38","author":"Bateson","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3939","DOI":"10.1080\/01431160110115960","article-title":"Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations","volume":"23","author":"Asner","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.rse.2005.01.002","article-title":"Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporate endmember variability?","volume":"95","author":"Song","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1016\/j.rse.2011.03.003","article-title":"Endmember variability in spectral mixture analysis: A review","volume":"115","author":"Somers","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"9523","DOI":"10.1029\/96JD00343","article-title":"A tractable physical model of shortwave radiation interception by vegetative canopies","volume":"101","author":"Roujean","year":"1996","journal-title":"J. Geophys. Res."},{"key":"ref_48","unstructured":"Ross, J. (2012). The Radiation Regime and Architecture of Plant Stands, Springer Science & Business Media."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"11201","DOI":"10.1029\/97JD00341","article-title":"Retrieval of land surface parameters from airborne polder bidirectional reflectance distribution function during hapex-sahel","volume":"102","author":"Roujean","year":"1997","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/0002-1571(71)90092-6","article-title":"A theoretical analysis of the frequency of gaps in plant stands","volume":"8","author":"Nilson","year":"1971","journal-title":"J. Agric. Meteorol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.rse.2005.05.003","article-title":"Global mapping of foliage clumping index using multi-angular satellite data","volume":"97","author":"Chen","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/0034-4257(84)90057-9","article-title":"Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model","volume":"16","author":"Verhoef","year":"1984","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"20455","DOI":"10.1029\/92JD01411","article-title":"A bidirectional reflectance model of the Earth\u2019s surface for the correction of remote sensing data","volume":"97","author":"Roujean","year":"1992","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3373","DOI":"10.1080\/01431169608949157","article-title":"Linear spectral mixture modelling to estimate vegetation amount from optical spectral data","volume":"17","author":"Gilabert","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","unstructured":"Camacho, F., Garc\u00eda-Haro, F.J., Fuster, B., and Sanchez-Zapero, J. (2019, September 09). MSG\/SEVIRI Vegetation Parameters (VEGA) Validation Report. SAF\/LAND\/UV\/VR_VEGA_MSG, v3.1. Available online: https:\/\/landsaf.ipma.pt\/en\/products\/vegetation\/."},{"key":"ref_56","unstructured":"Garc\u00eda-Haro, F.J., Camacho-de Coca, F., Meli\u00e1, J., and Mart\u00ednez, B. (2005, January 19\u201323). Operational derivation of vegetation products in the framework of the LSA SAF project. Proceedings of the 2005 EUMETSAT Meteorological Satellite Conference, Dubrovnik, Croatia."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.rse.2005.06.006","article-title":"The value of multiangle measurements for retrieving structurally and radiatively consistent properties of clouds, aerosols, and surfaces","volume":"97","author":"Diner","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.rse.2006.06.020","article-title":"Analysis of the MISR LAI\/FPAR product for spatial and temporal coverage, accuracy and consistency","volume":"107","author":"Hu","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1080\/02757250009532392","article-title":"Mathematical aspects of BRDF modeling: Adjoint problem and Green\u2019s function","volume":"18","author":"Knyazikhin","year":"2000","journal-title":"Rem. Sens. Rev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/S0034-4257(03)00009-9","article-title":"A new parameterization of canopy spectral response to incident solar radiation: Case study with hyperspectral data from pine dominant forest","volume":"85","author":"Wang","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.3390\/rs5031235","article-title":"Intercomparison of leaf area index products for a gradient of sub-humid to arid environments in West Africa","volume":"5","author":"Gessner","year":"2013","journal-title":"Remote Sens."},{"key":"ref_62","unstructured":"Camacho, F., Garc\u00eda-Haro, F.J., S\u00e1nchez-Zapero, J., Fuster, B., and Validation Report MSG\/SEVIRI Vegetation Parameters (VEGA) (2019, September 09). SAF\/LAND\/UV\/VR_VEGA_MSG, Issue 3.1. Available online: http:\/\/www.landsaf.meteo.pt."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Nightingale, J., Mittaz, J.P., Douglas, S., Dee, D., Ryder, J., Taylor, M., Old, C., Dieval, C., Fouron, C., and Duveau, G. (2019). Ten Priority Science Gaps in Assessing Climate Data Record Quality. Remote Sens., 11.","DOI":"10.3390\/rs11080986"},{"key":"ref_64","first-page":"463","article-title":"Inter-comparison and quality assessment of MERIS, MODIS and SEVIRI fAPAR products over the Iberian Peninsula","volume":"21","author":"Camacho","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2285","DOI":"10.1016\/j.rse.2009.06.009","article-title":"Prototyping of Land-SAF leaf area index algorithm with VEGETATION and MODIS data over Europe","volume":"113","author":"Verger","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1002\/2016JD024749","article-title":"Dynamics of water vapor and energy exchanges above two contrasting Sudanian climate ecosystems in Northern Benin (West Africa)","volume":"121","author":"Mamadou","year":"2016","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.pce.2016.03.007","article-title":"Application of satellite products and hydrological modelling for flood early warning","volume":"93","author":"Koriche","year":"2016","journal-title":"Phys. Chem. Earth"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2567","DOI":"10.5194\/hess-16-2567-2012","article-title":"Improving evapotranspiration in a land surface model using biophysical variables derived from MSG\/SEVIRI satellite","volume":"16","author":"Ghilain","year":"2012","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/TGRS.2013.2247611","article-title":"Deriving vegetation phenological time and trajectory information over Africa using SEVIRI daily LAI","volume":"52","author":"Guan","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1007\/s00382-016-3237-x","article-title":"Feedback of observed interannual vegetation change: A regional climate model analysis for the West African monsoon","volume":"48","author":"Klein","year":"2017","journal-title":"Clim. Dyn."},{"key":"ref_71","unstructured":"Arboleda, A., Ghilain, N., and Meulenberghs, F. (2019, July 12). First Product User Manual for MET&DMET (v2) and new LE&H products. Available online: SAF\/LAND\/RMI\/PUM\/ET&SF\/1.1, 2018, 35 pp."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1109\/TGRS.2007.905197","article-title":"Thermal land surface emissivity retrieved from SEVIRI\/METEOSAT","volume":"46","author":"Trigo","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_73","first-page":"124","article-title":"Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI\/MSG products","volume":"65","author":"Gilabert","year":"2018","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, B., Gilabert, M.A., S\u00e1nchez-Ruiz, S., Campos-Taberner, M., Garc\u00eda-Haro, F.J., Br\u00fcemmer, C., Carrara, A., Feig, G., Gr\u00fcnwald, T., and Mammarella, I. (2019). Evaluation of the LSA-SAF Gross Primary Production product derived from SEVIRI\/MSG data (MGPP). ISPRS J. Photogramm. Remote Sens., in review.","DOI":"10.1016\/j.isprsjprs.2019.11.010"},{"key":"ref_75","unstructured":"Garc\u00eda-Haro, F.J., Camacho, F., Verger, A., and Meli\u00e1, J. (2009, January 15\u201318). Current status and potential applications of the LSA-SAF suite of vegetation products. Proceedings of the 29th EARSeL Symposium, Chania, Greece."},{"key":"ref_76","unstructured":"Xie, P. (2001). CPC RFE Version 2.0. NOAA\/CPC Training Guide, Drought Monitoring Centre."},{"key":"ref_77","unstructured":"Laws, K.B., Janowiak, J.E., and Huffman, G.J. (2004, January 11\u201315). Verification of rainfall estimates over Africa using RFE, NASA MPA-RT, and CMORPH. Proceedings of the Combined Preprints CD-ROM, 84th AMS Annual Meeting, Paper P2.2 in 18th Conference on Hydrology, Seattle, WA, USA."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1016\/j.rse.2009.04.016","article-title":"Vegetation dynamics from NDVI time series analysis using the wavelet transform","volume":"113","author":"Gilabert","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/S0140-6736(11)61276-2","article-title":"Humanitarian response inadequate in Horn of Africa crisis","volume":"378","author":"Loewenberg","year":"2011","journal-title":"Lancet"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.crm.2017.03.006","article-title":"Understanding the evolution of the 2014\u20132016 summer rainfall seasons in southern Africa: Key lessons","volume":"16","author":"Archer","year":"2017","journal-title":"Clim. Risk Manag."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Qu, C., Hao, X., and Qu, J.J. (2019). Monitoring Extreme Agricultural Drought over the Horn of Africa (HOA) Using Remote Sensing Measurements. Remote Sens., 11.","DOI":"10.3390\/rs11080902"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"1610","DOI":"10.1111\/gcb.12807","article-title":"Ground and satellite-based evidence of the biophysical mechanisms behind the greening Sahel","volume":"21","author":"Brandt","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.gloplacha.2017.12.014","article-title":"Rainfall over the African continent from the 19th through the 21st century","volume":"165","author":"Nicholson","year":"2017","journal-title":"Glob. Planet. Chang."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2103\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:18:08Z","timestamp":1760188688000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2103"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,9]]},"references-count":83,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11182103"],"URL":"https:\/\/doi.org\/10.3390\/rs11182103","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,9,9]]}}}