LiDAR forestry mapping

Canopy coverage, biomass and species analyis among other forestry mapping solutions from LiDAR data

DIELMO 3D is developing innovative applications  for the Forestry Industry and the development of new “LiDAR forestry” algorithms, allowing for optimum results for each study area or proyect. All these developments implemented accordingly to large areas based on LiDAR data allow maximum reduction costs.

  • Forest Inventories
  • Forest segmentation
  • Fuel Models
  • Biomass
  • 3D forest structure
  • Custom algorithms for “LiDAR forestry”

LiDAR Forestry Inventory

Forest inventories using LiDAR data

Forest mapping solutions and development of custom APPs for inventories using LiDAR data. Analysis and parameters estimation for dominant height, FCC, nº of trees, treetop analysis, etc. as well as other deducted parameters (volumes, areas, etc.)

  • Forest inventory
  • Forest segmentation
  • Dominant height
  • FCC
  • Volumes
  • Custom analysis

3D forest structures

Voxel and 3D forest structures analysis

Thanks to the 3 dimension values provided by LiDAR, the forestry analysis can be in 3D using VOXELS (volumetric pixels) instead of bidimensional pixels information. The percent of points included within a voxel area provides valuable information for 3D analysis, for example tridimensional forest structures.

It is very important to analyze the 3D structure of the forest as it allows to estimate forest fires evolution, forest species richness. Moreover, other functional aspects of the forests as productivity are also related with the structure of the forest coverage.

Fuel models

Fuel models from LiDAR data

Thanks to the availability of a 3D forestr structure (see point above), it is possible to set a fuel model classification where, a LiDAR forestry point cloud, will allow us to find if there is vertical continuity or not between bushes and trees. LiDAR is also an added value for FCC analysis both for bushes and trees.


Biomass analysis and forest’s explotation optimisation

Edition of biomass typologies in order to generate high accurate mapping solutions for forestry for vegetation structure. The combination of this information with other factors (distances, slopes, etc) together with economical benefits factors (heating value of species, etc.) provides valuable information of where the forest explotation is efficient or not; and/or which biomass can be found in one area or another according to automated standard parameters.

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