Mapping beech ( Fagus sylvatica L . ) forest structure with airborne hyperspectral 1 imagery 2 3 Moses

11 12 The objective of this study was to assess the utility of hyperspectral data in 13 estimating and mapping forest structural parameters including mean diameter-at14 breast-height (DBH), mean tree height and tree density of a closed canopy beech 15 forest (Fagus sylvatica L). Airborne HyMap images and data on forest structural 16 attributes were collected from the Majella National Park, Italy in July 2004. The 17 predictive performances of normalised difference vegetation indices (NDVI) derived 18 from all possible two-band combinations were evaluated using calibration (n = 33) 19 and test (n = 20) data sets. The potential of partial least squares (PLS) regression was 20 also assessed. New NDVIs based on the contrast between reflectance in the red-edge 21 shoulder (756-820 nm) and the water absorption feature centred at 1200 nm (117222 1320 nm) were found to show higher correlations with the forest structural parameters 23 than standard NDVIs derived from NIR and visible reflectance. PLS regression 24 showed a slight improvement in estimating the beech forest structural attributes 25 compared to NDVI using linear regression models. Mean DBH was the best predicted 26 variable among the stand parameters (calibration R = 0.62 for an exponential model 27 fit and standard error of prediction = 5.12 cm, i.e. 25% of the mean). The predicted 28 map of mean DBH revealed high heterogeneity in the beech forest structure in the 29 study area. The DBH map could be useful to forest management in many ways e.g. 30 thinning of coppice to promote diameter growth, to assess the effects of management 31 on forest structure or to detect changes in the forest structure caused by anthropogenic 32 and natural factors. 33 34 35