Tree Health and Quality Assessment with LiDAR

Research using ground-based LiDAR for precision tree structure characterization and analytical framework to assess quality and health of hardwoods using LiDAR data.

ForestImageLiDAR.png

ABOVE: 3D point cloud composed of 12 million individual data points acquired with a single scan using terrestial LiDAR system (TLS) in the center of a mixed species planted stand at Martell Forest. Warmer colors correspond to taller portions of the canopy.


Principal Investigators

  • Brady Hardiman, Assistant Professor, Forestry & Natural Resources, Purdue University
  • Songlin Fei, Professor, Forestry & Natural Resources, Purdue University

External Collaborators

Research using feature-based high-resolution classification on multi-temporal data for planned and unplanned disturbance, including fire, wind-throw, and logging.

  • Ayman Habib, Professor, Civil Engineering, Purdue University
  • Joey Gallion, Forestry Inventory Program Manager, Indiana Department of Natural Resources
  • Gord McNickle, Assistant Professor, Botany & Plant Pathology, Purdue University

Objective

Develop a suite of tools including affordable, off-the-shelf TLS (terrestrial LiDAR systems) hardware and user-friendly analytical software that will ingest TLS data and output metrics of stand inventory and tree quality and health that are of interest and utility to both researchers and industry professionals.

Watch a webinar with Purdue experts talking about terrestrial remote sensing developments and applications in digital forestry.


Forestry and Natural Resources, 715 West State Street, West Lafayette, IN 47907-2061 USA, (765) 494-3590

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