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Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

Torbern Tagesson, Benjamin Smith, Anders Löfgren, Anja Rammig, Lars Eklundh and Anders Lindroth
Ambio
Vol. 38, No. 6 (Sep., 2009), pp. 316-324
Published by: Springer on behalf of Royal Swedish Academy of Sciences
Stable URL: http://www.jstor.org/stable/40390242
Page Count: 9
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Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing
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Abstract

The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologie data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.

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