Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices

Görner, Anna GND

Dissertation "Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices" Author: Anna Görner Abstract: Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using me- teorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. This study evaluates the effectiveness with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. The objective is to examine if known limitations such as dependence on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Fur- thermore, this thesis examines the effect of using different fraction of absorbed photosynthetically active radiation (faPAR) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. The conclusion of this study is that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, a universally applicable light use efficiency model based on MODIS PRI could not be established. Models that were optimised for a pool of data from several sites did not perform well.

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Görner, Anna: Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices. Jena 2011. MPI-BGC.

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