Estimation of forest stand characteristics using spectral histograms derived from an Ikonos satellite image

The aim of this paper was to examine the potential of Ikonos satellite images for estimating boreal forest stand characteristics using frequency distributions of radiometric values. The spectral features selected for use in the estimation were medians, standard deviations, and the parameters of the two-parametric Weibull distribution derived from the standwise spectral histograms of the Ikonos image. Ancillary map information, such as land-use and peatland classes, was also included. The method of estimation was non-parametric k-most similar neighbors (K-MSN) method. The most accurate results were achieved using spectral features that were derived from the multispectral images. The lowest RMSEs for the mean total stem volume, basal area, and mean height were 52.2 m³/ha (31.3 percent), 5.6 m²/ha (25.3 percent), and 3.1 m (20.6 percent), respectively. When only the panchromatic image was used in the analysis, the RMSEs for the mean total stem volume and basal area were about 3 percentage points higher. No differences in the mean height estimates were observed between the multispectral and panchromatic images. The most efficient predictor variables were the medians and the scale parameters of the Weibull distribution. The use of classified map information did not improve the results. The findings suggest that Ikonos satellite images can be used in to estimate forest stand characteristics giving an accuracy that corresponds to that achieved with aerial photographs.