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Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA) can contribute to overcoming this challenge. Reference OPEN ACCESSRemote Sens. 2015, 7 15362 fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA) and simulated Environmental Mapping and Analysis Program (EnMAP) and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%.

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<p>The north-East of Europe is affected by the ash (Fraxinus excelsior) dieback caused by the fungal pathogen Hymenoscyphus pseudoalbidus. A great variety of studies utilize remote sensing data and subsequently derived spectral indices to estimate the magnitude and spatial distribution of the damage for different tree types. </p><p>Often, structural indices, such as the NDVI are applied to detect already affected tree (sometimes even for early detection). However, there are differences in the suitability of an index. While a structural index, might have advantages when the canopy is not closed, pigment-based indices can show more variation within a full crown coverage forest. Therefore, the season of data acquisition might define the preferred index-selection. The same accounts not just for seasonal but for inter-annual changes, too. Here, the pigment indices show a higher sensitivity towards changes due to damages than structural indices.</p><p>To show these differences, the presented study is evaluating a variety of indices derived by hyperspectral imagery for affected ash trees in north-east Germany. This includes images from different phenological stages within one year (2015) and a comparison between 2011, 2015, and 2019 because the decline increased severely within this timespan for the observed trees. The indices were compared with tree damage estimations from the regional forest administration. </p><p>Preliminary results show a better relation for structural indices in autumn, but higher relation for pigment-based indices in spring and summer, once the crown is closed. A higher sensitivity to changes between 2011 and 2019 can be shown for pigment-based indices.</p>