The Leaf Area Index (LAI) is an important measure in many ecological applications because vegetation-atmosphere processes of the canopy, such as photosynthesis are controlled by the foliage and play an essential role in the carbon cycle. Therefore accurate determination of LAI is of great interest. Forest LAI is difficult to estimate due to the complex structure of the canopy and its high variability. Previous studies have shown that hemispherical photography is a useful technique to determine LAI by involving different gap fraction models but exposure seems to affect LAI estimates. Hemispherical photography and LAI-2000 plant canopy analyzer ground measurements were taken to capture the LAI at selected plots in the study site. The photographs were captured with two different exposure settings, namely manual and automatic, to examine the effects on LAI. Subsequently, we analyzed the photographs with the Software Hemisfer that allows the calculation of LAI with five different mathematical methods. Hemisfer was developed by the Swiss Federal Research Institute WSL. In order to obtain an LAI map of the study area, data of the airborne imaging spectrometer HyMap were used, acquired in summer 2004. Three images were recorded approximately at the same time, whereas two of them were North-South oriented and the third perpendicular to them. All HyMap data were preprocessed and across- track illumination variations were corrected. Six two-band Vegetation indices (eg. PVI, SAVI2) were exploited by developing regression models between ground-based LAI and VI’s. The VI with the best performance was then applied on HyMap data. The objectives of this study were (1) the evaluation of different mathematical methods to calculate LAI from hemispherical photographs, (2) the investigation of camera exposure influencing LAI estimates and (3) the examination of illumination effects on LAI when applying VI’s on HyMap data. The evaluation of the five different LAI calculation methods from hemispherical photographs showed that the coefficients of variation ranged from 10.69 % to 15.43 %. LAI derived with manual camera exposure settings correlated better (R2=0.97) with LAI-2000 values than LAI from automatically exposed photographs (R2=0.85). A comparison of the VI’s showed that good results were achieved with SAVI2 as well as with PVI. Investigating illumination effects on LAI indicated that although a correction has been performed, influences on LAI can still be observed.