Structural attributes of forest, such as canopy crown closure, stand height, stem density and basal area, derived from the third Spanish National Forest Inventory (IFN-3) were used in combination with spectral information derived from Landsat Enhanced Thematic Mapper Plus (ETM+) imagery and topographic information to evaluate their relationships. To deal with the variability found in the literature, three different types of vegetation, dominated by conifers, evergreen sclerophyll and broad-leaved deciduous trees, were analysed. In addition, the analyses were performed using three sets of plots filtered to be successively more homogeneous. A multivariate canonical ordination method, redundancy analysis (RDA), was used to enable the simultaneous evaluation of the two data sets and provide a useful graphical output highlighting the relationships between response (structural attributes) and explanatory (spectral and topographic) variables. Rank correlation analyses were also performed. The low percentage of explained variance at the multivariate analyses and low rank correlation coefficients made it difficult to derive practical empirical models. The strong influence of vegetation type on the results was confirmed, given that each type was sensitive to a different kind of spectral information. Finally, the results did not allow validation of the hypothesis that the relationship should be better when using a more homogeneous set of plots.