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Proceedings Paper

Investigating the performance of a low-cost thermal imager for forestry applications
Author(s): M. Smigaj; R. Gaulton; S. L. Barr; J. C. Suarez
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Paper Abstract

Thermography can be used for monitoring changes in the physiological state of plants. This is due to stress factors influencing emissions in the thermal infrared part of electromagnetic spectrum, and in effect changing the thermal properties of plants. However, there has been limited research into the use of thermal remote sensing approaches for tree health monitoring in the UK. This is due to a need for high spatial resolution data, which is usually obtained with low temporal frequency. Newly emerging technologies, such as unmanned aerial vehicles (UAVs), could supplement aerial data acquisition, but sensor development is still in the early stages. This paper investigates the performance of a low-cost microbolometer thermal infrared camera, which was to be deployed on a UAV platform. First the camera was tested in a laboratory environment to investigate whether camera temperature changes have a significant impact on the image quality. Tests suggested that a rapid camera’s temperature change is reflected in future images, but the expected temperature change rate experienced during UAV launch and altitude gain would not have significant effect on the quality of thermal imagery. Further field-based experiment showed that obtaining absolute temperatures of non-blackbody objects can be accurately performed with such camera, providing the emissivity of surfaces is accurately known. The variation in the target’s surface temperature throughout time was also well reflected.

Paper Details

Date Published: 18 October 2016
PDF: 11 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 100041E (18 October 2016); doi: 10.1117/12.2241417
Show Author Affiliations
M. Smigaj, Newcastle Univ. (United Kingdom)
R. Gaulton, Newcastle Univ. (United Kingdom)
S. L. Barr, Newcastle Univ. (United Kingdom)
J. C. Suarez, Forest Research (United Kingdom)


Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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