6533b856fe1ef96bd12b25a6

RESEARCH PRODUCT

Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula

Beatriz MartínezFrancisco Javier García-haroAleixandre VergerAleixandre VergerFernando CamachoMaría Amparo Gilabert

subject

Global and Planetary Changegeography.geographical_feature_category010504 meteorology & atmospheric sciencesQuality assessment0211 other engineering and technologiesPrimary production02 engineering and technologyLand cover15. Life on landManagement Monitoring Policy and Law01 natural sciencesTemporal consistencyGeographyPhotosynthetically active radiationPeninsulaClimatologyAbsolute biasSatelliteComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface Processes

description

Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.

https://doi.org/10.1016/j.jag.2012.06.010