Determining morphometric properties of radiata pine using long wave infrared sensing and biologically-inspired vision

Anthony Finn, Russell Brinkworth, Daniel Griffiths, Stefan Peters

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)
10 Downloads (Pure)


A miniaturised, high resolution visible and long wave infrared (LWIR) sensor was carried onboard an unmanned aerial vehicle to observe sections of radiata pine forests. The raw irradiance measurements were temporally pre-processed using a biologically-inspired vision (BIV) model to allow information within and across the images to be normalised. This permitted a larger, denser, and more tailored set of key points within the 2D image stacks to be corresponded, thereby improving 3D reconstructions of individual trees derived using structure from motion (SfM). The BIV model comprises multiple layers of processing derived from measured or assumed responses of the photoreceptor cells in the hoverfly. Its pre-processing expands the range of input signal obtained from the LWIR sensor and enhances foreground-background contrast. Morphological image processing techniques were also applied to enhance key image features before structure from motion is applied. The result allows structural properties of individual trees to be characterised in terms of their potential volume and quality; and contrasted with the point clouds obtained from the visible imagery that only depicts the tree canopies.

Original languageEnglish
Pages (from-to)277-281
Number of pages5
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Issue number2/W13
Publication statusPublished - 4 Jun 2019
Externally publishedYes
Event4th ISPRS Geospatial Week 2019 - Enschede, Netherlands
Duration: 10 Jun 201914 Jun 2019
Conference number: 4th

Bibliographical note

This work is distributed under the Creative Commons Attribution 4.0 License.


  • forestry
  • image processing
  • infrared sensor
  • remote sensing
  • UAVs


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