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Abstract: MODIS data are needed for the development of a light-use efficiency model over Swedish forests. Sweden stretches between Lat. 55N. and Lat. 69N. and MODIS reflectance data are recorded at vastly different sun and viewing angles. We have investigated modelled and observed red and near-infrared (NIR) MODIS data, and the normalised difference vegetation index (NDVI), in order to enable the development of a processing scheme that can be used for correcting MODIS data for directional effects. Directional reflectances have been simulated with the Kuusk–Nilson forest reflectance model, based on data from the Swedish National Forest Inventory. Modelled BRDF data are stored in a look-up table (LUT) and the possibility of finding a match with the observed data is tested. The analysis shows that matching may be based on normalised data rather than absolute values. Directional effects in the modelled data differ between sparse, medium and dense forest stands. The matching of observed MODIS data to the model data stored in the LUT is severely hampered by the scatter in the MODIS data. Reducing this scatter, e.g., by an improved cloud screening and improved atmospheric correction, will be necessary for the development of a reliable correction scheme. [Copyright &y& Elsevier]

Abstract: Forest leaf area index (LAI), is an important variable in carbon balance models. However, understory vegetation is a recognized problem that limits the accuracy of satellite-estimated forest LAI. A canopy reflectance model was used to investigate the impact of the understory vegetation on LAI estimated from reflectance values estimated from satellite sensor data. Reflectance spectra were produced by the model using detailed field data as input, i.e. forest LAI, tree structural parameters, and the composition, distribution and reflectance of the forest floor. Common deciduous and coniferous forest types in southern Sweden were investigated. A negative linear relationship (r 2 =0.6) was observed between field estimated LAI and the degree of understory vegetation, and the results indicated better agreement when coniferous and deciduous stands were analysed separately. The simulated spectra verified that the impact of the understory on the reflected signal from the top of the canopy is important; the reflectance values varying by up to ±18% in the red and up to ±10% in the near infra-red region of the spectra due to the understory. In order to predict the variation in LAI due to the understory vegetation, model inversions were performed where the input spectra were changed between the minimum, average and maximum reflectance values obtained from the forward runs. The resulting variation in LAI was found to be 1.6 units on average. The LAI of the understory could be predicted indirectly from simple stand data on forest characteristics, i.e. from allometric estimates, as an initial step in the process of estimating LAI. It is suggested here that compensation for the effect of the understory would improve the accuracy in the estimates of canopy LAI considerably. [Copyright &y& Elsevier]