Researchers are working to speed up automated tree measurement, using low-cost Optical Gauging System (LOGS) with stereo cameras and machine learning.

Principal Investigators

Guofan Shao | Professor of Remote Sensing
Keith Woeste | Adjunct Assistant Professor of Forestry
Yung-Hsiang Lu | Professor of Electrical and Computer Engineering


The long-term goal of this project is to develop a Low-cost Optical Gauging System (LOGS) for efficient forest inventory and data management.

  • Develop and demonstrate a portable device capable of real-time tree measurements of tree diameters at regular height intervals. Although the data processing of terrestrial stereoscopic photogrammetry is much faster than for the popular Structure from Motion (SfM) photogrammetry, it cannot yet provide “real time” output, which we consider essential.
  • Develop an algorithm to automatically locate (in a GIS framework) individual trees to avoid redundant tree measurements or skipped measurements on the ground. This functionality will also be helpful to take multiple measurements and obtain mean values for each tree, improving the accuracy of tree measurements.
  • Demonstrate the integrated system with a broad range of plantations and selected natural forest stands in Indiana. The system will be evaluated for use in a range of tree species and forest types.