23 June 2017 Thermal infrared imaging of the variability of canopy-air temperature difference distribution for heavy metal stress levels discrimination in rice
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Abstract
This paper addresses the assessment and interpretation of the canopy-air temperature difference ( T c - T a ) distribution as an indicator for discriminating between heavy metal stress levels. T c - T a distribution is simulated by coupling the energy balance equation with modified leaf angle distribution. Statistical indices including average value (AVG), standard deviation (SD), median, and span of T c - T a in the field of view of a digital thermal imager are calculated to describe T c - T a distribution quantitatively and, consequently, became the stress indicators. In the application, two grains of rice growing sites under “mild” and “severe” stress level were selected as study areas. A total of 96 thermal images obtained from the field measurements in the three growth stages were used for a separate application of a theoretical variation of T c - T a distribution. The results demonstrated that the statistical indices calculated from both simulated and measured data exhibited an upward trend as the stress level becomes serious because heavy metal stress would o
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Biyao Zhang, Biyao Zhang, Xiangnan Liu, Xiangnan Liu, Meiling Liu, Meiling Liu, Dongmin Wang, Dongmin Wang, } "Thermal infrared imaging of the variability of canopy-air temperature difference distribution for heavy metal stress levels discrimination in rice," Journal of Applied Remote Sensing 11(2), 026036 (23 June 2017). https://doi.org/10.1117/1.JRS.11.026036 . Submission: Received: 11 January 2017; Accepted: 6 June 2017
Received: 11 January 2017; Accepted: 6 June 2017; Published: 23 June 2017
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