Evaluation of MODIS gross primary productivity for Africa using eddy covariance data

Sjöström M., Zhao M., Archibald S., Arneth Almur, Cappelaere Bernard, Falk U., De Grandcourt Agnès, Hanan N., Kergoat Laurent, Kutsch Werner L., Merbold L., Mougin E., Nickless A., Nouvellon Yann, Scholes Robert J., Veenendaal Elmar M., Ardö Junas. 2013. Evaluation of MODIS gross primary productivity for Africa using eddy covariance data. Remote Sensing of Environment, 131 : 275-286.

Quartile : Q1, Sujet : REMOTE SENSING / Quartile : Q1, Sujet : IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY / Quartile : Q1, Sujet : ENVIRONMENTAL SCIENCES

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Géographie-Aménagement-Urbanisme-Architecture

Résumé : MOD17A2 provides operational gross primary production (GPP) data globally at 1 km spatial resolution and 8-day temporal resolution. MOD17A2 estimates GPP according to the light use efficiency (LUE) concept assuming a fixed maximum rate of carbon assimilation per unit photosynthetically active radiation absorbed by the vegetation (?max). Minimum temperature and vapor pressure deficit derived from meteorological data down-regulate ?max and constrain carbon assimilation. This data is useful for regional to global studies of the terrestrial carbon budget, climate change and natural resources. In this study we evaluated the MOD17A2 product and its driver data by using in situ measurements of meteorology and eddy covariance GPP for 12 African sites. MOD17A2 agreed well with eddy covariance GPP for wet sites. Overall, seasonality was well captured but MOD17A2 GPP was underestimated for the dry sites located in the Sahel region. Replacing the meteorological driver data derived from coarse resolution reanalysis data with tower measurements reduced MOD17A2 GPP uncertainties, however, the underestimations at the dry sites persisted. Inferred ?max calculated from tower data was higher than the ?max prescribed in MOD17A2. This, in addition to uncertainties in fraction of absorbed photosynthetically active radiation (FAPAR) explains some of the underestimations. The results suggest that improved quality of driver data, but primarily a readjustment of the parameters in the biome parameter look-up table (BPLUT) may be needed to better estimate GPP for African ecosystems in MOD17A2.

Mots-clés Agrovoc : productivité primaire, modèle de simulation, modèle mathématique, conditions météorologiques, cycle du carbone, télédétection

Mots-clés géographiques Agrovoc : Afrique, Sahel

Classification Agris : U10 - Informatique, mathématiques et statistiques
P01 - Conservation de la nature et ressources foncières

Champ stratégique Cirad : Axe 6 (2005-2013) - Agriculture, environnement, nature et sociétés

Auteurs et affiliations

• Sjöström M., Lund University (SWE)
• Zhao M., University of Maryland (USA)
• Archibald S., CSIR (ZAF)
• Arneth Almur, Karlsruhe Institute of Technology (DEU)
• Cappelaere Bernard, IRD (FRA)
• Falk U., Universität Bonn (DEU)
• De Grandcourt Agnès, CRDPI (COG)
• Hanan N., Geographic Information Science Center of Excellence (USA)
• Kergoat Laurent, GET (FRA)
• Kutsch Werner L., Johann Heinrich von Thunen-Institut (DEU)
• Merbold L., ETH (CHE)
• Mougin E., GET (FRA)
• Nickless A., CSIR (ZAF)
• Nouvellon Yann, CIRAD-PERSYST-UMR Eco&Sols (BRA)
• Scholes Robert J., CSIR (ZAF)
• Veenendaal Elmar M., Wageningen Agricultural University (NLD)
• Ardö Junas, Lund University (SWE)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/567134/)

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