Outlook for the Single-Tree-Level Forest Inventory in Nordic Countries

Assessing the Dependencies of Scots Pine (Pinus sylvestris L.) Structural Characteristics and Internal Wood Property Variation

“…Therefore, previous research has mainly focused on linking growth characteristics (e.g., diameter increment) to wood density variation [11,13,19,20] and rarely utilized detailed size or shape characteristics, or competition status of a tree. The methodological development within the last two decades using terrestrial laser scanning (TLS) acquired three-dimensional data to describe the external architecture of an individual tree [21][22][23][24][25][26] or tree communities [27][28][29][30][31][32] has reached the point where characterization of tree crown and branch properties [33][34][35][36][37] in addition to the stem taper measurements [21,25,[38][39][40] are possible. However, Pyörälä et al [35,36] concluded that comprehensive branch distribution of a tree remains challenging to capture due to the occlusion effect and increasing distance to the scanner at higher parts of the living crown, thus, reducing the quality of a TLS point cloud.…”

Close-Range Remote Sensing of Forests: The state of the art, challenges, and opportunities for systems and data acquisitions

“…Due to the static data acquisition pattern, i.e., measuring on a tripod at a single location, TLS is suitable for collecting data from small areas (e.g., sample plots) and individual trees at LoD 3 [27], i.e., suborder branches. Therefore, its most prominent application in forest sciences is acquiring auxiliary information, e.g., stem tapering and quality attributes [31], and detailed references for modeling that are costly to measure with traditional means or require destructive sampling [27], [54]- [56]. This section focuses on the most recent developments on plot and tree levels after 2016, when a TLS-specific review was published, e.g., [27].…”

Lidar Boosts 3D Ecological Observations and Modelings: A Review and Perspective

“…Many of the structural attributes derived from lidar data avoid the saturation effect that is typical for passive optical sensors and may even challenge the accuracy of traditional field measurements [115]- [117]. For example, the accuracy of TLS DBH measurements was reported to range from 0.74 to 3.51 cm and tree height measurements from 1.36 to 6.53 m [38], [118], [119]. The accuracy of TLS measurements is primarily influenced by the density and accuracy of point clouds, tree density, and forest type [120], [121].…”