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פותח על ידי קלירמאש פתרונות בע"מ -
Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields
Year:
2011
Source of publication :
GRASPA Working papers
Authors :
אלחנתי, ויקטור
;
.
כהן, אביהו
;
.
כהן, יפית
;
.
Volume :
Co-Authors:

Levi, Ofer; Naor, Amos

Facilitators :
From page:
1
To page:
4
(
Total pages:
4
)
Abstract:

Detection of variability in agricultural fields depends on the spatial scale of the observed variable. Plant water status can be evaluated using thermal IR images that can provide valuable information on the water status, whereas visible RGB images can provide detailed information on the plants' color, which is not a good indicator of the water status. The informative mode (thermal IR images) has coarse resolution, as opposed to the excessive resolution of the less informative mode (visible RGB). In the present study, we present a method to enhance the information obtained from the thermal IR mode, by combining information from the visible RGB mode. We propose to un-mix the temperature of objects in the thermal images based on the information extracted from the high resolution RGB image.

Note:
Related Files :
Agricultural crops
remote sensing
Spatial variability
Thermal analysis
עוד תגיות
תוכן קשור
More details
DOI :
Article number:
0
Affiliations:
Database:
גוגל סקולר
Publication Type:
מאמר מתוך כינוס
;
.
Language:
אנגלית
Editors' remarks:
ID:
36610
Last updated date:
02/03/2022 17:27
Creation date:
14/08/2018 10:49
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Scientific Publication
Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields

Levi, Ofer; Naor, Amos

Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields

Detection of variability in agricultural fields depends on the spatial scale of the observed variable. Plant water status can be evaluated using thermal IR images that can provide valuable information on the water status, whereas visible RGB images can provide detailed information on the plants' color, which is not a good indicator of the water status. The informative mode (thermal IR images) has coarse resolution, as opposed to the excessive resolution of the less informative mode (visible RGB). In the present study, we present a method to enhance the information obtained from the thermal IR mode, by combining information from the visible RGB mode. We propose to un-mix the temperature of objects in the thermal images based on the information extracted from the high resolution RGB image.

Scientific Publication
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