Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)

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Martinez , B , Gilabert , M A , Sanchez-Ruiz , S , Campos-Taberner , M , Garcia-Haro , F J , Bruemmer , C , Carrara , A , Feig , G , Gruenwald , T , Mammarella , I & Tagesson , T 2020 , ' Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP) ' , ISPRS Journal of Photogrammetry and Remote Sensing , vol. 159 , pp. 220-236 . https://doi.org/10.1016/j.isprsjprs.2019.11.010

Title: Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)
Author: Martinez, B.; Gilabert, M. A.; Sanchez-Ruiz, S.; Campos-Taberner, M.; Garcia-Haro, F. J.; Bruemmer, C.; Carrara, A.; Feig, G.; Gruenwald, T.; Mammarella, I.; Tagesson, T.
Contributor: University of Helsinki, Staff Services
Date: 2020-01
Language: eng
Number of pages: 17
Belongs to series: ISPRS Journal of Photogrammetry and Remote Sensing
ISSN: 0924-2716
URI: http://hdl.handle.net/10138/314145
Abstract: The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. A parameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of photosynthesis as a consequence of water stress. A three years data record (2015–2017) was used in an assessment against site-level eddy covariance (EC) tower GPP estimates and against other Earth Observation (EO) based GPP products. The site-level comparison indicated that the MGPP product performed better than the other EO based GPP products with 48% of the observations being below the optimal accuracy (absolute error < 1.0 g m−2 day−1) and 75% of these data being below the user requirement threshold (absolute error < 3.0 g m−2 day−1). The largest discrepancies between the MGPP product and the other GPP products were found for forests whereas small differences were observed for the other land cover types. The integration of this GPP product with the ensemble of LSA-SAF MSG products is conducive to meet user needs for a better understanding of ecosystem processes and for improved understanding of anthropogenic impact on ecosystem services.
Subject: 114 Physical sciences
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