Calculating Crop Water Stress Index Using Remote Sensing

8/14/2019 Calculating Crop Water Stress Index Using Remote Sensing

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Calculating CropCalculating CropWater Stress IndexWater Stress Index

Christopher Kruse


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OverviewOverview1. Background, Motivation

2. Calculating CWSI3. Results Temperature Data


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IntroductionIntroductionTwo assumptions of the CWSI:1. As a crop transpires, the evaporation ofwater cools the leaves below the air

temperature.2. As a crop becomes water stressed, thetranspiration will decrease and thetemperature will then increase (Jackson 1982).


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Crop Water Stress IndexCrop Water Stress Index

WheredT is the difference between the canopy temperature

and the air temperature (Tc - Ta),

dTu is the upper limit of Tc - Ta (non-transpiring), and

dT1 is the lower limit of Tc - Ta (well-watered).

0 CWSI 1


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ParametersParameters- For dT, fieldcalibratedtemperature data

(thanks to Cassie)used for Tc comes

from the MASTERthermal data.

- The airtemperaturesmeasured from theCIMIS station inBelridge are used


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Params cont.Params cont.

- The green line showswhere the Tc - Ta would

indicate maximumstress for soybeans.

- The blue line showsthe Tc - Ta value that

would indicate lowstress for a given Vapor

Pressure Deficit (VPD).

U.S. Water Conservation


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ResultsResults- The main input I was interested in wasthe temperatures from MASTER.

- The temperatures after the first

calibration were high and unrealistic.

- The temperatures after the secondcalibration were lower and realistic.


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ResultsResults- The image to the left shows thedifference between the atmospherically

corrected and the first field calibratedcanopy temperature from MASTER and airtemperature from the CIMIS station (31.7C).

- The test field is the lower field.

- Most of the values positive. The averageTc Ta for the test field was 5.019598 C.

Average temp in the test field of 5.02 C is


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ProblemsProblems- The image to the left shows the locationof the thermal gun measurements and theregions used for the canopy temperaturecalibration.- Thermal data from three trees were

available. The temperature values fromthe surrounding nine pixels wereaveraged.

- The difference of MASTER and thermalgun temperatures were then calculated

and averaged.

-


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More ResultsMore Results- Both plots show T

c T

a.

- The one on the left is beforethe canopy calibration and theone on the right is after.


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More ResultsMore Results- This image was created using the secondfield calibration.

- Most of the values negative. Theaverage Tc Ta for the test field was

-3.517924 C.


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Final ResultsFinal Results- This image shows the CWSI based on theprevious temperatures.

Min 0.000000

Max 0.708980Mean 0.213831Stdev 0.071707

An average valueof 0.214 wouldindicate low stress.


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Final ResultsFinal Results

0.599423 0.239932


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ConclusionsConclusionsThe CWSI values calculated with the averageddifference temperature calibration and the finaltemperature calibration were very comparable.

Temperature data that is much higher than expected

could possibly be calibrated to the canopytemperature if actual measurements of the canopytemperatures are available.

The final calibration of the temperature resulted incanopy temperatures lower than the airtemperature.

Both the averaged difference calibration and the

final calibration temperatures resulted in CWSI


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ThanksThanksI would like to thank Shawn and Susan for all of theirhelp with this project.

I would also like to thank the other members of ourgroup for their help.

I would also like to thank everyone who made theStudent Airborne Research Program work.

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Calculating Crop Water Stress Index Using Remote Sensing