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Lund University (2012)

Satellite remote sensing of primary production in semi-arid Africa

Sjöström Martin

Titre : Satellite remote sensing of primary production in semi-arid Africa

Auteur : Sjöström Martin

University : Lund University

Grade : Doctor of Philosophy (PhD) 2012

With the challenges Africa faces with respect to the predicted warming due to climate change, the continents role in the global carbon cycle has been increasingly recognized. Earth observing satellites have played a significant role in the study of vegetation, particularly in Africa where climate stations are sparse. Satellite data can provide the means to map plant primary production for monitoring of food and grazing resources and to elucidate the role of African regions in the global carbon cycle. In this thesis, remote sensing based methods for large area estimation of primary production have been evaluated, primarily in semi-arid African ecosystems, by using the light use efficiency concept. Furthermore, the degree to which environmental driving forces account for a satellite observed greening trend in the African Sahel (a semi-arid region located between the Sahara and the more tropical areas to the south) from 1982 to 1998 was investigated by using a dynamic global vegetation model (DGVM). The DGVM simulations re-enforce the hypothesis that the greening as observed by satellites is related to rainfall. Although this suggests that an increase in rainfall is the dominant causative factor of the greening, the analysis was based on aggregated data. Finer observations from the moderate resolution imaging spectroradiometer (MODIS) may be used to provide more detailed measures of primary production. An overall relationship was found between eddy covariance gross primary production (GPP, the total amount of carbon assimilated through photosynthesis by plants) and the MODIS enhanced vegetation index (EVI). However, the incorporation of measurements of photosynthetically active radiation (PAR), and a water availability factor to EVI improved relationships with eddy covariance GPP. Site specific relationships to GPP with all of these variables included were found to be explained by peak leaf area index (LAI) and long-term mean annual rainfall. In addition, the MODIS GPP model was evaluated over African sites. This model estimates GPP according to the light use efficiency approach and assumes a fixed maximum rate of carbon assimilated per unit PAR absorbed (epsilon max) for different biomes. MODIS GPP correlated well with eddy covariance GPP for some sites and seasonality was generally well captured. However, GPP was underestimated for the drier sites. The underestimations were concluded to be mainly due to low values of epsilon max but can also be due to the linear interpolation of fraction of absorbed photosynthetically active radiation (FAPAR) across unreliable values. Continued efforts of land surface validation are needed to improve models driven by satellite data over semi-arid ecosystems. To better link estimates of carbon with reflectance properties, installation of radiometric instruments at eddy covariance sites would be beneficial

Mots clés : primary production, remote sensing, vegetation index, savanna, grassland


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