Calculating Crop Water Stress Index Using Remote Sensing
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Calculating Crop Water Stress Index using remote sensing Christopher Kruse
Overview 1. 2. 3. 4.
Background, Motivation Calculating CWSI Results – Temperature Data Problems – Temperature Data
Introduction Two assumptions of the CWSI: 1. As a crop transpires, the evaporation of water cools the leaves below the air temperature. 2. As a crop becomes water stressed, the transpiration will decrease and the temperature will then increase (Jackson 1982). Using remote sensing to see the crop surface
Crop Water Stress Index (CWSI) Where dT 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
Parameters - For dT, field calibrated temperature data (thanks to Cassie) used for Tc comes from the MASTER thermal data. - The air temperatures measured from the CIMIS station in Belridge are used for Ta .
Params cont. - The green line shows where the Tc - Ta would indicate maximum stress for soybeans. - The blue line shows the Tc - Ta value that would indicate low stress for a given Vapor Pressure Deficit (VPD).
U.S. Water Conservation Laboratory
Params cont.
- According to the U.S. Water Conservation Lab, the upper limit of Tc – Ta can be calculated by:
Where rs is aerodynamic resistance (s m-1 ), Rn the net radiation (W m-2), G is the soil heat flux (W m-2 ), Y is the density of air (kg m-3 ), and Cp is the heat capacity of air (~1013 J kg-1 °C-1 ).
Params cont. The lower limit of this difference can be calculated by
Where K is the psychrometric “constant” (kPa °C-1 ), “-” is the slope of the saturated vapor pressure-temperature relation (kPa °C-1 ), VPD is the vapor pressure deficit (kPa). Equations for K, “-”, and VPD are not shown.
Results - The main input I was interested in was the temperatures from MASTER. - The temperatures after the first calibration were high and unrealistic. - The temperatures after the second calibration were lower and realistic.
Results
- The image to the left shows the difference between the atmospherically corrected and the first field calibrated canopy temperature from MASTER and air temperature from the CIMIS station (31.7 °C). - The test field is the lower field. - Most of the values positive. The average Tc – Ta for the test field was 5.019598 °C. Average temp in the test field of 5.02 °C is a problem!
Problems - The image to the left shows the location of the thermal gun measurements and the regions used for the canopy temperature calibration. - Thermal data from three trees were available. The temperature values from the surrounding nine pixels were averaged. - The difference of MASTER and thermal gun temperatures were then calculated and averaged. - The average difference (7.86667 °C) was
More Results - Both plots show Tc – Ta. - The one on the left is before the canopy calibration and the one on the right is after.
More Results - Both of these images show the CWSI - The image on the left shows the CWSI before the canopy calibration and the image on the right shows after the calibration.
More Results - This image was created using the second field calibration. - Most of the values negative. The average Tc – Ta for the test field was -3.517924 °C.
Final Results - This image shows the CWSI based on the previous temperatures.
Min – 0.000000 Max – 0.708980 Mean – 0.213831 Stdev – 0.071707 An average value of 0.214 would indicate low stress.
Final Results
0.599423 0.213831
0.239932
Conclusions The CWSI values calculated with the averaged difference temperature calibration and the final temperature calibration were very comparable. Temperature data that is much higher than expected could possibly be calibrated to the canopy temperature if actual measurements of the canopy temperatures are available. The final calibration of the temperature resulted in canopy temperatures lower than the air temperature. Both the averaged difference calibration and the final calibration temperatures resulted in CWSI
Thanks I would like to thank Shawn and Susan for all of their help with this project. I would also like to thank the other members of our group for their help. I would also like to thank everyone who made the Student Airborne Research Program work.
Overview 1. 2. 3. 4.
Background, Motivation Calculating CWSI Results – Temperature Data Problems – Temperature Data
Introduction Two assumptions of the CWSI: 1. As a crop transpires, the evaporation of water cools the leaves below the air temperature. 2. As a crop becomes water stressed, the transpiration will decrease and the temperature will then increase (Jackson 1982). Using remote sensing to see the crop surface
Crop Water Stress Index (CWSI) Where dT 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
Parameters - For dT, field calibrated temperature data (thanks to Cassie) used for Tc comes from the MASTER thermal data. - The air temperatures measured from the CIMIS station in Belridge are used for Ta .
Params cont. - The green line shows where the Tc - Ta would indicate maximum stress for soybeans. - The blue line shows the Tc - Ta value that would indicate low stress for a given Vapor Pressure Deficit (VPD).
U.S. Water Conservation Laboratory
Params cont.
- According to the U.S. Water Conservation Lab, the upper limit of Tc – Ta can be calculated by:
Where rs is aerodynamic resistance (s m-1 ), Rn the net radiation (W m-2), G is the soil heat flux (W m-2 ), Y is the density of air (kg m-3 ), and Cp is the heat capacity of air (~1013 J kg-1 °C-1 ).
Params cont. The lower limit of this difference can be calculated by
Where K is the psychrometric “constant” (kPa °C-1 ), “-” is the slope of the saturated vapor pressure-temperature relation (kPa °C-1 ), VPD is the vapor pressure deficit (kPa). Equations for K, “-”, and VPD are not shown.
Results - The main input I was interested in was the temperatures from MASTER. - The temperatures after the first calibration were high and unrealistic. - The temperatures after the second calibration were lower and realistic.
Results
- The image to the left shows the difference between the atmospherically corrected and the first field calibrated canopy temperature from MASTER and air temperature from the CIMIS station (31.7 °C). - The test field is the lower field. - Most of the values positive. The average Tc – Ta for the test field was 5.019598 °C. Average temp in the test field of 5.02 °C is a problem!
Problems - The image to the left shows the location of the thermal gun measurements and the regions used for the canopy temperature calibration. - Thermal data from three trees were available. The temperature values from the surrounding nine pixels were averaged. - The difference of MASTER and thermal gun temperatures were then calculated and averaged. - The average difference (7.86667 °C) was
More Results - Both plots show Tc – Ta. - The one on the left is before the canopy calibration and the one on the right is after.
More Results - Both of these images show the CWSI - The image on the left shows the CWSI before the canopy calibration and the image on the right shows after the calibration.
More Results - This image was created using the second field calibration. - Most of the values negative. The average Tc – Ta for the test field was -3.517924 °C.
Final Results - This image shows the CWSI based on the previous temperatures.
Min – 0.000000 Max – 0.708980 Mean – 0.213831 Stdev – 0.071707 An average value of 0.214 would indicate low stress.
Final Results
0.599423 0.213831
0.239932
Conclusions The CWSI values calculated with the averaged difference temperature calibration and the final temperature calibration were very comparable. Temperature data that is much higher than expected could possibly be calibrated to the canopy temperature if actual measurements of the canopy temperatures are available. The final calibration of the temperature resulted in canopy temperatures lower than the air temperature. Both the averaged difference calibration and the final calibration temperatures resulted in CWSI
Thanks I would like to thank Shawn and Susan for all of their help with this project. I would also like to thank the other members of our group for their help. I would also like to thank everyone who made the Student Airborne Research Program work.
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