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Canopy temperature interpretation of thermal imagery for crop water stress determination
Year:
2009
Authors :
Alchanatis, Victor
;
.
Cohen, Yafit
;
.
Volume :
Co-Authors:
Meron, M., MIGAL Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Tsipris, J., MIGAL Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Alchanatis, V., Institute of Agricultural Engineering, ARO, Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Cohen, Y., Institute of Agricultural Engineering, ARO, Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Facilitators :
From page:
63
To page:
70
(
Total pages:
8
)
Abstract:
Crop water stress determination methods from canopy temperatures, derived from the surface energy balance equations, treat the canopy temperature as the 'big-leaf', under the assumption that the canopy behaves as a single homogeneous virtual leaf, covering the surface. Introduction of very high resolution thermal imagery, 0.01 to 0.3 m pixel size, acquired from low altitude platforms, enabled finely detailed measurement of the whole canopy, raising the question how to select the relevant temperatures. One approach is to select the sunlit leaves confirming to the 'big leaf' energy balance paradigm. However, thermal imagery alone lacks part of the information, and needs additional marking or synchronized visible imagery, making the process complicated and expensive. The other approach is to use full frame pixel statistics without pattern recognition, by selecting the mean temperature of the cold fraction from the pixel histogram,. That greatly simplifies processing for large scale aerial thermography. In irrigation experiments conducted on cotton and vine grapes, both approaches were tested in parallel. Ground referenced thermal and visible images were overlapped, and sunlit, shaded and whole canopy leaves were selected for crop temperature evaluation. The pixel histograms of the same images were analyzed for the mean temperatures of the lowest 33% and 100% of the pixels, after discarding soil related 7 ° C higher than air temperature pixels. Several crop water stress indices (CWSI) were compared to leaf (LWP) and stem water potentials (SWP) and stomatal conductance. CWSI values determined in grape vines by either image segmentation or histogram analysis methods correlated well with SWP and stomatal conductance, with closely similar correlation coefficients. In cotton, CWSI determined by histogram analysis was more sensitive stress indicator than LWP. The equal suitability of both methods in canopy temperature evaluation for crop water stress evaluation was demonstrated.
Note:
Related Files :
correlation coefficient
Crops
irrigation
Pattern Recognition
Reference surfaces
Stem water potentials
Stomatal conductance
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Related Content
More details
DOI :
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
31136
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 01:00
Scientific Publication
Canopy temperature interpretation of thermal imagery for crop water stress determination
Meron, M., MIGAL Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Tsipris, J., MIGAL Galilee Technology Center, P.O. Box 831, Kiryat Shmona 11016, Israel
Alchanatis, V., Institute of Agricultural Engineering, ARO, Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Cohen, Y., Institute of Agricultural Engineering, ARO, Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Canopy temperature interpretation of thermal imagery for crop water stress determination
Crop water stress determination methods from canopy temperatures, derived from the surface energy balance equations, treat the canopy temperature as the 'big-leaf', under the assumption that the canopy behaves as a single homogeneous virtual leaf, covering the surface. Introduction of very high resolution thermal imagery, 0.01 to 0.3 m pixel size, acquired from low altitude platforms, enabled finely detailed measurement of the whole canopy, raising the question how to select the relevant temperatures. One approach is to select the sunlit leaves confirming to the 'big leaf' energy balance paradigm. However, thermal imagery alone lacks part of the information, and needs additional marking or synchronized visible imagery, making the process complicated and expensive. The other approach is to use full frame pixel statistics without pattern recognition, by selecting the mean temperature of the cold fraction from the pixel histogram,. That greatly simplifies processing for large scale aerial thermography. In irrigation experiments conducted on cotton and vine grapes, both approaches were tested in parallel. Ground referenced thermal and visible images were overlapped, and sunlit, shaded and whole canopy leaves were selected for crop temperature evaluation. The pixel histograms of the same images were analyzed for the mean temperatures of the lowest 33% and 100% of the pixels, after discarding soil related 7 ° C higher than air temperature pixels. Several crop water stress indices (CWSI) were compared to leaf (LWP) and stem water potentials (SWP) and stomatal conductance. CWSI values determined in grape vines by either image segmentation or histogram analysis methods correlated well with SWP and stomatal conductance, with closely similar correlation coefficients. In cotton, CWSI determined by histogram analysis was more sensitive stress indicator than LWP. The equal suitability of both methods in canopy temperature evaluation for crop water stress evaluation was demonstrated.
Scientific Publication
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