Forest structural diversity characterization in Mediterranean pines of Central Spain with QuickBird-2 imagery and canonical correlation analysis

Variation in forest structure provides information on vegetation complexity and provides insights on biodiversity. Characterizing forest structural diversity with remotely sensed data supports reporting, monitoring, and policy development. We explored the relationship between forest structural diversity in Mediterranean pines of the Spanish Central Range and variables derived from imagery captured with a commercial high spatial resolution satellite (QuickBird-2; with pixels sided 2.4 m multispectral and 0.68 m panchromatic). To combine multiple aspects of tree conditions at a stand level, “structural diversity” was characterized at the plot level (N = 1022) as a linear combination of the median of absolute differences of individual trees’ bole diameter, height, and crown diameter measured on the field from the local median equivalents. Spectral reflectance variations in the visible and near-infrared, as well as image co-occurrence texture metrics from the panchromatic imagery at various window sizes were generated. All relationships to image-derived values were assessed against circular 0.3 ha areas corresponding with the field measured plots. Canonical correlation analysis aided in identification of combinations of reflectance and texture metrics most highly related with forest structural diversity (R = 0.89). Reflectance diversity was found to be more important than co-occurrence texture features in describing forest structural diversity when forest structure was limited (R = 0.47 vs. R = 0.39), whereas texture was more informative to the model when the forest structural diversity was high (R = 0.88 vs. R = 0.63), relating more complex forest conditions. Our results, although empirically defined by the local conditions and image acquisition characteristics, demonstrated the potential in high spatial resolution imagery for description of forest structural diversity in forests of the Mediterranean environment, especially important for Spain where a national high spatial resolution image data base has been collected.