Fig. 1
From: Classifying development stages of primeval European beech forests: is clustering a useful tool?

Biplots of the first principal components (PC) of inventory data of two primeval beech forests (7 attributes, see Table 2). The colored area and the contour lines represent PC-scores. Arrows depict PC-loadings. A moving window was used to aggregate the datasets from completely mapped data at four observation scales (window sizes; separated by grey shaded areas). Contour lines mark areas with equal point densities (in total 8216 points in Mirdita and 9666 points in Rajca). Coloring represents the results of k-means clustering with 3 clusters (red, green and blue; color mixing indicates overlap of two or more clusters). A uniform kernel was used for the moving window (equal weighting of all objects within the window). For results of a bivariate normal kernel (weighting of objects by their distance to the window center) see Additional file 1: Figure S1