We have released “DF LAT”, software for LiDAR data processing

We have released “DF LAT”, software for LiDAR data processing of forest.

DeepForest Technologies Co., Ltd. (CEO: Masanori Onishi) collaborated with Professor Yusuke Onoda and Dr. Md Farhadur Rahman of Kyoto University to develop “DF LAT” (DeepForest LiDAR Tool), a software that analyzes point cloud data captured by drone LiDAR and converts it into actionable forest information.

DF LAT is a software tool that generates detailed forest analysis data from point cloud data acquired by drone-mounted LiDAR.
It processes LiDAR data in LAS format (.las) captured by drones to detect ground and vegetation, and automatically creates:

  • Digital Terrain Models (DTM)

  • Digital Surface Models (DSM)

  • Canopy Height Models (CHM)

This enables efficient generation of high-resolution topographic and forest structure information for advanced forest analysis.

 

Typically, airborne LiDAR surveys produce models with a resolution of around 50 cm.
Using drone-mounted LiDAR in combination with DF LAT, it is possible to obtain 3D data with a resolution of 5 cm.
This allows the creation of high-resolution terrain maps that capture forest trails and micro-topography, as well as detailed canopy height models that can distinguish individual trees.

DF LAT also enables cross-sectional views at any desired location, and manual filtering can be applied to remove noise that automated processing may not eliminate.

 

The data generated by DF LAT can be used in combination with DF Scanner, DeepForest’s forest analysis software, to detect individual trees, identify species, and estimate attributes such as tree height and volume for each tree.
When measurement requirements are met, the data can also be used to support Japan carbon credit applications.

The software is available for download via the link below, and a license is required for use.

https://www.df-webservice.com/product/select

 

This research and development was supported by the following grant:

  • Japan Society for the Promotion of Science (JSPS) KAKENHI JP21H05314, “Innovative Integrated Approaches of Genomics, Traits, and Ecology for Maximizing Forest Functions” (Project Leader: Yusuke Onoda)