Abstract
Obtaining average canopy temperature (Tc) by thresholding canopy pixels from on-ground thermal imagery has historically been undertaken using ‘wet’ and ‘dry’ reference surfaces in the field (reference temperature thresholding). However, this method is extremely time inefficient and can suffer inaccuracies if the surfaces are non-standardised or unable to stabilise with the environment. The research presented in this paper evaluates non-reference techniques to obtain average canopy temperature (Tc) from thermal imagery of avocado trees, both for the shaded side and sunlit side, without the need of reference temperature values. A sample of 510 thermal images (from 130 avocado trees) were acquired with a FLIR B250 handheld thermal imaging camera. Two methods based on temperature histograms were evaluated for removing non-canopy-related pixel information from the analysis, enabling Tc to be determined. These approaches included: 1) Histogram gradient thresholding based on temperature intensity changes (HG); and 2) histogram thresholding at one or more standard deviation (SD) above and below the mean. The HG method was found to be more accurate (R2 > 0.95) than the SD method in defining canopy pixels and calculating Tc from each thermal image (shaded and sunlit) when compared to the standard reference temperature thresholding method. The results from this study present an alternative non-reference method for determining Tc from ground-based thermal imagery without the need of calibration surfaces. As such, it offers a more efficient and computationally autonomous method that will ultimately support the greater adoption of non-invasive thermal technologies within a precision agricultural system.
Highlights
In agriculture, the average canopy temperature (Tc) extracted from digital thermal imagery (TI) is increasingly being used to non-destructively quantify plant water status and help in the more efficient irrigation of crops [1,2,3,4,5]
The histogram gradient (HG) method presented in this study offers a histogram method for thresholding canopy pixels from thermal images that produces results comparable to those from the accepted reference temperature (RT) thresholding method
The results from this study present an alternative, histogram method for thresholding canopy area from ground-based thermal imagery without the need of temperatures from reference surfaces
Summary
The average canopy temperature (Tc) extracted from digital thermal imagery (TI) is increasingly being used to non-destructively quantify plant water status and help in the more efficient irrigation of crops [1,2,3,4,5]. Specialised image analysis software that often accompanies the thermal cameras, e.g., FLIR QuickReport®, Reporter Pro®, and FLIR ThermaCAMTM Researcher software (FLIR Systems, USA) [7,8], can be used to undertake a limited amount of thermal image pre-processing These software packages generally provide only basic computation functions such as providing mean, maximum, and minimum temperatures from specified regions of interests (ROI) that are typically manually defined by the user for each image [7,9]. A methodology to sort the canopy pixels in thermal imagery is the use of coincident red, green, and blue (RGB) colour images [10,11] This process does require an RGB image to be acquired at precisely the same time as the thermal image, to account for slight changes in orientation as a result of external factors such as wind. If the mask is not accurate, the extracted Tc may be influenced by the inclusion of non-canopy-specific and mixed pixels
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
