Browsing by Subject "hakkuukonekoeala-aineisto"

A diameter distribution describes the size distribution of a forest and is used, for example, in forest planning. Stand characteristics can also be produced without a diameter distribution, but the diameter distribution allows utilization of tree-level models in the calculation of stand level variables and improves the estimation accuracy. In this thesis estimation methods for diameter distribution prediction were compared and the suitability of the methods and materials evaluated by using error indices. The two comparative diameter distribution estimation methods used in this study were the k most similar neighbor method (k-MSN) and the prediction of diameter distribution using the theoretical distribution model: Weibull-distribution. Both study methods utilised laser scanning-, field plot- and harvester measurement data collected from mature Norway spruce dominant forests in Southern Finland. When the k-MSN method is applied, the measured diameter distribution and stand characteristics of the nearest neighbor were imputed to the target grid of the stand. Stand characteristics were used for the prediction of Weibull-distribution parameters. Weibull parameters were estimated by modelling and by parameter recovery. Field and harvester plots were used as a reference data for the k-MSN. The suitability of the Weibull distribution for the description of the diameter distribution was evaluated by estimating the diameter distribution directly on the harvester data of the corresponding region. Maximum likelihood estimation and prediction of the Weibull-distribution were applied. As a result of the suitability testing, the Weibull distribution is seen as suitable for describing the diameter distribution of a mature, even aged, stand. With the maximum likelihood method and parameter recovery, the produced diameter distribution corresponded appropriately with the measured diameter distribution. The results of the k-MSN show that the imputation of diameter distribution gave the most accurate prediction of diameter distribution. Harvester or field plots gave nearly as accurate results and are both suitable for diameter distribution prediction