Airborne laser scanning based forest inventory for forest management by applying novel metrics and multiple data source

The aim of this work was to develop airborne laser scanning (ALS) based forest inventory for practical forest management by applying novel horizontal metrics and multiple data sources. In particular, this work examined classification of forest land attributes (study I), prediction of species-specific stand attributes (study II) and detection of spatial pattern of trees (study III) and need for silvicultural operations, such as first thinning (study III) and tending of seedling stand (study IV). An area-based approach was used together with different classification or prediction methods in all studies. Multiple data sources were used to calculate a combination of predictor variables: in study I ALS data and satellite images, in study II ALS data, aerial images and stand register data, and in study IV ALS data and aerial images. The applicability of horizontal ALS-based metrics was tested in studies I and III. In study I the applicability of field data from national forest inventory of Finland as a training data was also tested. The classification of land use/land cover classes was highly accurate. Also, classification of site fertility type, peatland type and drainage status succeeded moderately well. The prediction of species-specific stand attributes of several tree species was more accurate when tree species proportions from existing stand register data were used in prediction. The classification accuracies were very high for the spatial pattern of trees and need for first thinning, and moderately high for the need for tending of seedling stands. Horizontal ALS-based metrics were the most applicable predictor variables in classification of land use/land cover, main land type, drainage status, detection of spatial pattern of trees and need for first thinning. To conclude, this work provided valuable methodological know-how on the applicability of novel horizontal ALS-based metrics and the use of multiple data sources for cost-effective forest inventory and planning. Some of the methods have already been implemented in practical forest inventories in Finland.