The aim of the studies in this thesis was to apply and further develop methods in multi-source forest inventory tasks in boreal and tropical forests. The applications presented in this dissertation are based on optical remote sensing data and k-nearest neighbours techniques, both of which are common components in multi-source forest inventory.
The use of variograms as a texture information source in standwise volume estimation was tested using image data from a digitized aerial photograph taken in Hyytiälä, Finland. According to the leave one out cross-validation, the accuracy of volume estimation at stand level improved when empirical values of semivariance were included in the set of feature variables.
Landsat 5 Thematic Mapper (TM) satellite data was utilized in forest cover and volume mapping in Terai, Nepal. A corresponding multi-source forest inventory-oriented processing chain was also tested and demonstrated in forest volume mapping in the region of Kon Tum province in Vietnam. In these two studies, coarse scale MODIS reflectance products were used as a reference in a local correction approach conducted for the relative calibration of Landsat TM images.
Multi-source forest inventory techniques for obtaining biomass maps have facilitated the development of a spatially explicit methodology to estimate the bioenergy potentials of forest chips. The technical bioenergy potential of forest chips was calculated in a case study in Central Finland, based on the logging residues and stumps from final fellings.
An adaptation of the abovementioned methods and techniques in studies with target areas of forests in sub-tropical and tropical zones in Nepal and Vietnam was carried out using open source software tools. These studies serve the purpose of capacity building in utilizing remote sensing data in forest inventory activities related to the REDD+ mechanism, and estimating bioenergy potentials provides quantitative decision making support in the field of forest bioenergy production