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פותח על ידי קלירמאש פתרונות בע"מ -
Estimating cotton water consumption using a time series of Sentinel-2 imagery
Year:
2018
Source of publication :
Agricultural Water Management
Authors :
היימן, ניתאי
;
.
טנאי, יוסף
;
.
קפלן, גריגורי
;
.
רוזנשטיין, עופר
;
.
Volume :
207
Co-Authors:
Facilitators :
From page:
44
To page:
52
(
Total pages:
9
)
Abstract:

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management. Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance. In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse. Kc was estimated as the ratio between reference evapotranspiration and the measured cotton evapotranspiration. In addition, a time series of Sentinel-2 imagery was processed to produce 22 vegetation indices (VIs) based on the sensor's unique spectral bands. Empirical Kc – VI models were derived and ranked according to their prediction error. In accordance with previous studies, we found a strong correlation between the normalized difference vegetation index (NDVI) and Kc (R2 = 0.94), and yet, we also identified other spectral indices that are more strongly correlated to Kc. The indices that were found to be the most suitable for Kc prediction were based on the red and red-edge bands (MTCI, REP, and S2REP). This progress in estimating cotton water consumption using satellite imagery that are available at no cost is a leap forward towards the development of crop irrigation requirements models. Consequently, this work sets the scene for near-real-time irrigation decision support systems. © 2018 Elsevier B.V.

Note:
Related Files :
Artificial intelligence
Crops
Decision support systems
evapotranspiration
irrigation
remote sensing
עוד תגיות
תוכן קשור
More details
DOI :
10.1016/j.agwat.2018.05.017
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
34693
Last updated date:
02/03/2022 17:27
Creation date:
03/07/2018 12:16
Scientific Publication
Estimating cotton water consumption using a time series of Sentinel-2 imagery
207 .
Estimating cotton water consumption using a time series of Sentinel-2 imagery .

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management. Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance. In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse. Kc was estimated as the ratio between reference evapotranspiration and the measured cotton evapotranspiration. In addition, a time series of Sentinel-2 imagery was processed to produce 22 vegetation indices (VIs) based on the sensor's unique spectral bands. Empirical Kc – VI models were derived and ranked according to their prediction error. In accordance with previous studies, we found a strong correlation between the normalized difference vegetation index (NDVI) and Kc (R2 = 0.94), and yet, we also identified other spectral indices that are more strongly correlated to Kc. The indices that were found to be the most suitable for Kc prediction were based on the red and red-edge bands (MTCI, REP, and S2REP). This progress in estimating cotton water consumption using satellite imagery that are available at no cost is a leap forward towards the development of crop irrigation requirements models. Consequently, this work sets the scene for near-real-time irrigation decision support systems. © 2018 Elsevier B.V.

Scientific Publication
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