Browsing by Subject "ajouralaskenta"

Up-to-date forest inventory benefits the entire forest industry, all the way from forest owners to buyers of raw wood. The forest inventory gathered through remote sensing data and field sample plots by both National Forest Inventory (NFI) and Finnish Forest Centre supports large-scale strategic planning of forestry management and creates a foundation for forest planning as well as up-to-date forest inventory. Operative planning and up-to-date forest inventory also require information about recent cuttings. Finnish Forest Centre has deemed it necessary to develop tools to monitor the realized cuttings on an annual basis. The aim is that data from annual forest operations and cuttings could be transferred into updated forest inventory as soon as possible. The main focus of this thesis was on a method developed by Metsäteho Oy, whereby a stand delineation is automatically created for each forest stand based on harvester data (Melkas ym. 2020). Stand delineation carried out on the basis of stem-specific harvester location data would enable to constantly update the forest inventory in conjunction with logging operations. Stand delineation is an important information because stand area is routinely used as a coefficient in the estimation of stand-specific logging accumulation (Belbo & Talbot 2020). The harvester data was gathered between December 2017 and June 2018 and comprised approximately 3,000 harvested objects and 5,316,214 locations all over continental Finland. The stem-spesific location data recorded by harvester is used in automated stand delineation. Using triangulation, the location data of the stands was combined into a network, and a buffer zone was created for the resulting polygon to reduce the contribution of errors in GNSS navigation while also reflecting the reach of the harvester boom. The use of harvester location data also made it possible to automatically create a strip road network, which in turn allowed to calculate stand-specific strip road variables. Compared to aerial photography references, automated delineation yielded reliable stand delineations when carried out with three most common logging methods and when the stand area was at least .75 hectares. The automated stand was on average three per cent larger than the reference stand manually created from digital aerial photographs. Compared to reference stands, the relative areas of the automated stands were as follows: 1.044 for the first thinning; 1.020 for later thinnings; 1.034 for clear cutting; and 1.031 for all of these harvesting methods combined. There was little variation between the various harvesting methods, and the correlation between automated stand areas and references increased with the size of the stand. For stands with an area more than 1.5 hectares the relative difference in areas was, on average, only around one per cent. Another aim was the validation of automated strip road calculation. On the basis of harvester locations, a strip road network was created, where the to-and-fro movement of the harvester was ignored. Next, the automatically created strip road network was used to calculate the average spacings between strip roads (in metres) and strip road density (in metres/hectare). This was done comprehensively for each stand. In addition, the strip road variables were calculated by emulating sample plot measurements carried out by the Finnish Forest Centre in the evaluation of the quality of harvesting sites objects. Both results were realistic when compared to best practices in forest management. On average, the spacing between strip roads in thinning areas was 20.7 metres and 17.1 metres in clear cuttings. To sum up, there was a reliable correlation between automated stand delineation and reference stands both in terms of area and location; thus, it would be viable to integrate the automatically delineated stands as part of reliable and up-to-date forest inventory. The results of strip road calculation are applicable to validate the implementation of the recommendations set for strip road networks.