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קהילה:
אסיף מאגר המחקר החקלאי
פותח על ידי קלירמאש פתרונות בע"מ -
Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces
Year:
2010
Authors :
אלחנתי, ויקטור
;
.
כהן, יפית
;
.
Volume :
11
Co-Authors:
Meron, M., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Tsipris, J., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Orlov, V., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Alchanatis, V., Institute of Agricultural and Environmental Engineering, Agricultural Research Organization, Volcani Center, Bet Dagan, Israel
Cohen, Y., Institute of Agricultural and Environmental Engineering, Agricultural Research Organization, Volcani Center, Bet Dagan, Israel
Facilitators :
From page:
148
To page:
162
(
Total pages:
15
)
Abstract:
Variable-rate irrigation by machines or solid set systems has become technically feasible, however mapping crop water status is necessary to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide such maps in sufficient detail and in a timely way. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high-resolution thermal imagery and artificial reference surfaces. Canopy-related pixels were separated from those of the soil by upper and lower thresholds related to air temperature, and canopy temperatures were calculated from the coldest 33% of the pixel histogram. Artificial surfaces that had been wetted provided reference temperatures for the crop water stress index (CWSI) normalized to ambient conditions. Leaf water potentials of cotton were related linearly to CWSI values with R2 = 0.816. Maps of crop stress level generated from aerial scans of cotton, process tomatoes and peanut fields corresponded well with both ground-based observations by the farm operators and irrigation history. Numeric quantification of stress levels was provided to support decisions to divide fields into sections for spatially variable irrigation scheduling. © 2010 Springer Science+Business Media, LLC.
Note:
Related Files :
aerial survey
Arachis hypogaea
Crop Production
Crop water stress index (CWSI)
Hula Valley
Israel
water stress
עוד תגיות
תוכן קשור
More details
DOI :
10.1007/s11119-009-9153-x
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
32406
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 01:09
Scientific Publication
Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces
11
Meron, M., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Tsipris, J., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Orlov, V., Crop Ecology Laboratory, MIGAL Galilee Technology Center, PO Box 831, Kiryat Shmona, Israel
Alchanatis, V., Institute of Agricultural and Environmental Engineering, Agricultural Research Organization, Volcani Center, Bet Dagan, Israel
Cohen, Y., Institute of Agricultural and Environmental Engineering, Agricultural Research Organization, Volcani Center, Bet Dagan, Israel
Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces
Variable-rate irrigation by machines or solid set systems has become technically feasible, however mapping crop water status is necessary to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide such maps in sufficient detail and in a timely way. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high-resolution thermal imagery and artificial reference surfaces. Canopy-related pixels were separated from those of the soil by upper and lower thresholds related to air temperature, and canopy temperatures were calculated from the coldest 33% of the pixel histogram. Artificial surfaces that had been wetted provided reference temperatures for the crop water stress index (CWSI) normalized to ambient conditions. Leaf water potentials of cotton were related linearly to CWSI values with R2 = 0.816. Maps of crop stress level generated from aerial scans of cotton, process tomatoes and peanut fields corresponded well with both ground-based observations by the farm operators and irrigation history. Numeric quantification of stress levels was provided to support decisions to divide fields into sections for spatially variable irrigation scheduling. © 2010 Springer Science+Business Media, LLC.
Scientific Publication
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