Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 349-354, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/349/2015/
doi:10.5194/isprsarchives-XL-3-W3-349-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
19 Aug 2015
UAV-BORNE THERMAL IMAGING FOR FOREST HEALTH MONITORING: DETECTION OF DISEASE-INDUCED CANOPY TEMPERATURE INCREASE
M. Smigaj1, R. Gaulton1, S. L. Barr1, and J. C. Suárez2 1School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK ITU, Civil Engineering
2Forest Research, Northern Research Station, Roslin, Midlothian, EH25 9SY, UK
Keywords: Stress detection, unmanned aerial vehicle, unmanned aerial system, UAV, UAS, camera calibration Abstract. Climate change has a major influence on forest health and growth, by indirectly affecting the distribution and abundance of forest pathogens, as well as the severity of tree diseases. Temperature rise and changes in precipitation may also allow the ranges of some species to expand, resulting in the introduction of non-native invasive species, which pose a significant risk to forests worldwide. The detection and robust monitoring of affected forest stands is therefore crucial for allowing management interventions to reduce the spread of infections.

This paper investigates the use of a low-cost fixed-wing UAV-borne thermal system for monitoring disease-induced canopy temperature rise. Initially, camera calibration was performed revealing a significant overestimation (by over 1 K) of the temperature readings and a non-uniformity (exceeding 1 K) across the imagery. These effects have been minimised with a two-point calibration technique ensuring the offsets of mean image temperature readings from blackbody temperature did not exceed ± 0.23 K, whilst 95.4% of all the image pixels fell within ± 0.14 K (average) of mean temperature reading.

The derived calibration parameters were applied to a test data set of UAV-borne imagery acquired over a Scots pine stand, representing a range of Red Band Needle Blight infection levels. At canopy level, the comparison of tree crown temperature recorded by a UAV-borne infrared camera suggests a small temperature increase related to disease progression (R = 0.527, p = 0.001); indicating that UAV-borne cameras might be able to detect sub-degree temperature differences induced by disease onset.

Conference paper (PDF, 1492 KB)


Citation: Smigaj, M., Gaulton, R., Barr, S. L., and Suárez, J. C.: UAV-BORNE THERMAL IMAGING FOR FOREST HEALTH MONITORING: DETECTION OF DISEASE-INDUCED CANOPY TEMPERATURE INCREASE, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 349-354, doi:10.5194/isprsarchives-XL-3-W3-349-2015, 2015.

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