Sweden consists of almost 68% of forests. It is the duty of private forest owners and companies to manage the forest in the best way and ensure sustainable forest production. Mobile laser scanning is a relatively new method for quick and easy documentation of the forest and for extracting important parameters for volume calculation and visualization using data processing.  In this study, five different walking patterns are compared when scanning a pine forest with a handheld laser scanner to evaluate which pattern that generates the most accurate data, densest point cloud, and most time efficiency. Data were collected in a well-managed pine forest west of Årsunda, in Gävleborg County during April 2023, in a 5,64-meter radius circle. The point clouds from the hand-held laser scanner and the different walking patterns were compared with data from a scanning with a terrestrial laser scanner on the same day. The diameter at breast height (DBH) for all trees in the study circle, visualization of point clouds and scanning time were compared.  The study resulted in one walking pattern that provided the lowest uncertainty and another that provided the clearest visualization. The walking pattern that resulted in the lowest uncertainty was easy and quick to both plan and execute, it also had the lowest average deviation from the reference data, only 1 cm, which can be considered very good. The second walking pattern, which generated the best visual appearance, also received a relatively small mean deviation. During the study, it became clear that certain parameters are affected by the person performing the scan and the speed at which it is performed. When it comes to presenting the results, the pros and cons depend on what the collected data is to be used for. Some walking patterns yield good results in some respects and worse in other. Therefore, all different parameters are compared in the discussion and broad results are presented.

Intresset för olika hyggesfria skogsbruksmetoder ökar men frågan är hur en skogsbruksplan kan anpassas till detta och vilken metod som kan användas. Denna studie inriktade sig på att mäta i fullskiktade skogar med enkla verktyg för att få ut beståndsdata till nytta för skötseln och att användas till en skogsbruksplan. För att få fram diameterspridningen klavades träden. Det krävdes minst 600 m2 för att få tillräcklig kvalitet i diameterspridning. För volymen jämfördes klavning, relaskopmätning och laserdata. Resultatet visade att det är svårt att mäta volym i fullskiktade bestånd beroende på tätheten och ojämnheten. Inte minst gäller detta relaskopmätning som undervärderade volymen. Klavning och laserdata fick ungefär samma precision. Studien visade också att tidsåtgången i fält för klavning jämfört med vanlig planläggning med relaskop endast skiljde några få minuter. Om klavning kombineras med att hämta volymen från laserdata kan till och med denna metod vara mer tidseffektiv.

Estimation of forest parameters using remote sensing information could streamline the forest industry from a time and economic perspective. This thesis utilizes object detection and semantic segmentation to detect and classify individual trees from images over 3D models reconstructed from satellite images. This thesis investigated two methods that showed different strengths in detecting and classifying trees in deciduous, evergreen, or mixed forests. These methods are not just valuable for forest inventory but can be greatly useful for telecommunication companies and in defense and intelligence applications. This thesis also presents methods for estimating tree volume and estimating tree growth in 3D models. The results from the methods show the potential to be used in forest management. Finally, this thesis shows several benefits of managing a digitalized forest, economically, environmentally, and socially.