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Evaluation of the L...
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Martínez, BeatrizUniversity of Valencia
(author)
Evaluation of the LSA-SAF Gross Primary Production product derived from SEVIRI/MSG data (MGPP)
- Article/chapterEnglish2020
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LIBRIS-ID:oai:lup.lub.lu.se:3438a599-4805-460a-bee0-6080fa73338c
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https://lup.lub.lu.se/record/3438a599-4805-460a-bee0-6080fa73338cURI
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https://doi.org/10.1016/j.isprsjprs.2019.11.010DOI
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Language:English
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Summary in:English &Swedish
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Subject category:art swepub-publicationtype
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Subject category:ref swepub-contenttype
Notes
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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 SurfaceAnalysis 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 absorbedphotosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. Aparameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioningunder optimal conditions, and a coefficient quantifying the reduction of photosynthesis as a consequence ofwater 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 comparisonindicated that the MGPP product performed better than the other EO based GPP products with 48% ofthe observations being below the optimal accuracy (absolute error < 1.0 g m−2 day−1) and 75% of these databeing below the user requirement threshold (absolute error < 3.0 g m−2 day−1). The largest discrepanciesbetween the MGPP product and the other GPP products were found for forests whereas small differences wereobserved for the other land cover types. The integration of this GPP product with the ensemble of LSA-SAF MSG
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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.
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Amparo Gilabert, MaríaUniversity of Valencia
(author)
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Sánchez-Ruiz, SergioUniversity of Valencia
(author)
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Campos-Taberner, M.University of Valencia
(author)
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García-Haro, Francisco JavierUniversity of Valencia
(author)
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Bruemmer, C.Thünen Institute of Climate-Smart Agriculture
(author)
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Carrara, A.Fundacion Centro de Estudios Ambientales del Mediterraneo (CEAM)
(author)
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Feig, GregorUniversity of Pretoria,Council of Scientific and Industrial Research (CSIR)
(author)
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Grünwald, T.Dresden University of Technology
(author)
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Mammarella, IUniversity of Helsinki
(author)
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Tagesson, TorbernLund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science(Swepub:lu)to5874ta
(author)
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University of ValenciaThünen Institute of Climate-Smart Agriculture
(creator_code:org_t)
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In:ISPRS Journal of Photogrammetry and Remote Sensing: Elsevier BV159, s. 220-2360924-2716
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