Table 5 Factors to consider for forest scanning and for choosing equipment according to objectives. DBH Diameter at breast height, LAI leaf area index, LAD leaf area density

Plot-level forest inventory

DBH / Basal area, stem profiles, stem volumes

High stem density, presence of understorey, heavy branching, corrugated ground (missing diameters, partial profiles)

Scanning in leaf-off conditions (if possible), scanning in acceptable wind conditions (<20kmh), possible with single scan method, more accurate with multiple scans method

Wide field-of-view, high acquisition speed, suitability for intensive campaigns (ergonomics, autonomy, weight)

Circle / cylinder fitting Voxel approaches Meshing processes

Stem detection and location, stem density,

High stem density, presence of understorey, heavy branching, corrugated ground (hidden trunks)

Circle / cylinder fitting

tree height

Direct measurements on point clouds

Species recognition, external wood defects recognition (Bark texture analysis)

Fine scanning resolution, RGB information

RGB camera

Dedicated algorithms

Canopy characterisation

Gap fraction

Leaf clumping (biases in gap fraction estimates)

Fine scanning resolution, acceptable wind conditions (<20kmh), thin laser beam

Hemispherical field-of-view, low beam divergence, last return / full waveform rangefinder

Point computation

LAI / LAD foliage stratification

Leaf clumping, leaf inclination angles, presence of non-photosynthetic tissues (biases in LAI and LAD estimates)

Multiple scan method, fine scanning resolution, acceptable wind conditions (no wind for leaf angles), separating leafy and woody material, thin laser beam

Infrared wavelength (1,000–1,500 nm), low beam divergence, last return / full waveform rangefinder

Separating leafy and woody points from intensity values, voxel / ray-tracing approaches

Detailed plant description

Woody tree architecture

Heavy branching (discontinuity)

Scanning in leaf-off conditions (if possible), multiple scans method, acceptable wind conditions (no wind for thin branches)

High acquisition speed (reduces wind effect)

Circle / cylinder fitting, voxel approaches, meshing processes

Entire leafy tree

Heavy branching, presence of foliage (non-visible internal tree structure)

Multiple scans method, fine scanning resolution, separating leafy and woody material, thin laser beam

Infrared wavelength (1,000–1,500 nm), low beam divergence, last return / full waveform rangefinder

Separating leafy and woody points from intensity values, voxel / ray-tracing approaches