Data combination and feature selection for multi-source forest inventory

Both satellite images and aerial photographs are now used operationally in Finland's forestry for different tasks; satellite images are used for national forest inventory purposes and aerial images for forest management planning. Due to the double coverage, it could be advantageous to utilize the strengths of both image types. The aim of this study was to evaluate the potential of the combination of Landsat ETM+ spectral and aerial photograph spectral and textural features for forest variable estimation. The studied stand variables were mean height, basal area per hectare, and the volume of the growing stock. Several approaches were tested when combining the image data sources: feature selection, feature weighting, satellite image-based stratification, and combination of individual estimates by weighting. The highest accuracies were obtained when both data sources were used. There were several good ways to combine the data sources, Feature selection with genetic algorithm and subsequent feature weighting gave the lowest mean volume RMSE (63.7 m(3)/ha, 65.3 percent of the mean).