Foliage temperature extraction from thermal imagery for crop water stress determination

2013 ◽  
Vol 14 (5) ◽  
pp. 467-477 ◽  
Author(s):  
M. Meron ◽  
M. Sprintsin ◽  
J. Tsipris ◽  
V. Alchanatis ◽  
Y. Cohen
Keyword(s):  
Water Stress ◽  
Stress Determination ◽  
Crop Water ◽  
Thermal Imagery ◽  
Crop Water Stress

Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces

2010 ◽  
Vol 11 (2) ◽  
pp. 148-162 ◽  
Author(s):  
M. Meron ◽  
J. Tsipris ◽  
Valerie Orlov ◽  
V. Alchanatis ◽  
Yafit Cohen
Keyword(s):  
Water Stress ◽  
Crop Water ◽  
Thermal Imagery ◽  
Site Specific ◽  
Stress Mapping ◽  
Crop Water Stress

Simple Background Subtraction of Thermal Imagery for Canopy Temperature Measurement in Greenhouse

2019 ◽  
Vol 35 (3) ◽  
pp. 339-344
Author(s):  
Kendall C DeJonge ◽  
Huihui Huihui Zhang ◽  
Sean M Gleason
Keyword(s):  
Water Stress ◽  
Canopy Temperature ◽  
Irrigation Scheduling ◽  
Small Scale ◽  
Crop Water ◽  
Thermal Imagery ◽  
Infrared Thermometry ◽  
Background Temperature ◽  
Homogeneous Background ◽  
Crop Water Stress

Abstract. While infrared thermometry and thermal imagery have potential to detect crop water stress and quantify evapotranspiration, both valuable in irrigation scheduling, it is often difficult to isolate plant canopy temperature from background temperatures. In this study, we demonstrate a simple technique that uses a homogeneous background temperature that contrasts with canopy temperature, thereby allowing the canopy temperature itself to be isolated in a thermal image. Analysis of pixel temperatures and their associated statistics demonstrate the potential of this method to measure small (ca. < 0.5°C) and rapid (ca. < 1 s) fluctuations in leaf energy balance. This technique has broad applicability in greenhouse, growth chamber, and other small-scale experiments where real time response of individual leaves or canopies is required. Keywords: Thermal imaging, Crop water stress, Infrared thermometry, Background masking, Deficit irrigation, Greenhouse.

Remote sensing and machine learning for crop water stress determination in various crops: a critical review

2020 ◽  
Vol 21 (5) ◽  
pp. 1121-1155 ◽  
Author(s):  
Shyamal S. Virnodkar ◽  
Vinod K. Pachghare ◽  
V. C. Patil ◽  
Sunil Kumar Jha
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Water Stress ◽  
Critical Review ◽  
Stress Determination ◽  
Crop Water ◽  
Crop Water Stress

scholarly journals Water Stress Regime of Irrigated Crops Based on Remote Sensing and Ground-Based Data

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1117
Author(s):  
Anatoly Mikhailovich Zeyliger ◽  
Olga Sergeevna Ermolaeva
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Crop Yield ◽  
Satellite Monitoring ◽  
Agricultural Crop ◽  
Crop Water ◽  
Stress Regime ◽  
Irrigation Water Use ◽  
Crop Water Stress ◽  
Crop Irrigation

In the past few decades, combinations of remote sensing technologies with ground-based methods have become available for use at the level of irrigated fields. These approaches allow an evaluation of crop water stress dynamics and irrigation water use efficiency. In this study, remotely sensed and ground-based data were used to develop a method of crop water stress assessment and analysis. Input datasets of this method were based on the results of ground-based and satellite monitoring in 2012. Required datasets were collected for 19 irrigated alfalfa crops in the second year of growth at three study sites located in Saratovskoe Zavolzhie (Saratov Oblast, Russia). Collected datasets were applied to calculate the dynamics of daily crop water stress coefficients for all studied crops, thereby characterizing the efficiency of crop irrigation. Accordingly, data on the crop yield of three harvests were used. An analysis of the results revealed a linear relationship between the crop yield of three cuts and the average value of the water stress coefficient. Further application of this method may be directed toward analyzing the effectiveness of irrigation practices and the operational management of agricultural crop irrigation.

An insight to the performance of crop water stress index for olive trees

2013 ◽  
Vol 118 ◽  
pp. 79-86 ◽  
Author(s):  
N. Agam ◽  
Y. Cohen ◽  
J.A.J. Berni ◽  
V. Alchanatis ◽  
D. Kool ◽  
...  
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Olive Trees ◽  
Crop Water Stress

Evaluation of Resistances for Bermudagrass Turf Crop Water Stress Index Models

1994 ◽  
Vol 86 (3) ◽  
pp. 574-581 ◽  
Author(s):  
H. R. Jalali‐Farahani ◽  
D. C. Slack ◽  
D. M. Kopec ◽  
A. D. Matthias ◽  
P. W. Brown
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress

Quantifying Wheat Water Stress with the Crop Water Stress Index to Schedule Irrigations

1994 ◽  
Vol 86 (1) ◽  
pp. 195-199 ◽  
Author(s):  
Donald J. Garrot ◽  
Michael J. Ottman ◽  
D.D. Fangmeier ◽  
Stephen H. Husman
Keyword(s):  
Water Stress ◽  
Stress Index ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Water Stress Index ◽  
Crop Water Stress
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