Reports

Various sensors measuring NDVI have been installed across the Delta sites over the last several years. At some sites, the SRS sensors from Decagon/METER have been drifting low, so I wanted to compare them with other NDVI measurements.

• SRS sensor (Decagon/METER): A pair of photodiodes with cosine correcting Teflon diffuser and hemispherical view. Red band is measured at 650nm and NIR band is measured at 810nm.
• SR-411 sensor (Apogee): A pair of photodiodes with acrylic diffuser and hemispherical view. Red band is measured at 650nm and NIR band is measured at 810nm.
• Planet Labs data: L3H (CESTEM) alpha data product. Pixel size is 3m, and there are daily gap-filled images from 2018-2020. Gap fills are done with Planet imagery from the day before and after, combined with daily MODIS data. From the full image, Joe cut out a 730mx730m tile for each site, centered on the tower. Product includes NDVI, GCC, ECI, and the following reflectances: red, NIR, green, blue. For more information, see Box/Biometlab/Remote_Sensing/PlanetLabs/L3H_distribution_lodi_islands_readme.pdf.
• Broadband NDVI: NDVI calculated using reflected SW and PAR data from the tower, called "broadband" because it uses the broader bands of shortwave and PAR radiation rather than the narrow bands of the SRS and Apogee sensors. See Huemmrich et al., 1999 in Journal of Geophysical Research: Atmospheres and Tittebrand et al., 2009 in Theoretical and Applied Climatology.

For some sites with I also compared GCC with the various NDVI values to see how much GCC values varied year over year. Photos were taken by a variety of cameras: Netcam Stardot cameras (the official camera of the Phenocam Network®), Canon point-and-shoot cameras with custom firmware, or a Raspberry Pi camera.

I used Joe's datafetch tool to calculate daily average mid-day values of NDVI and GCC from the various sensors. Mid-day values included data from 11:00 to 13:00, 5 values a day. I despiked the data in Excel.

• NDVI = (NIR-Red)/(NIR+Red)
• GCC = (Green)/(Red + Green + Blue)
• Broadband NDVI = (rho_NIR-rho_PAR)/(rho_NIR+rho_PAR)
  • rho_NIR= (SWout-PARout)/(SWin-PARin)
  • rho_PAR=(PARout/PARin)
  • Units of both SW and PAR should be in W/m2. Use the conversion 4.6 umol/m2/s = 1 W/m2 to convert the usual PAR units (umol/m2/s) to W/m2.

See reports for other Delta sites here:

Bouldin Alfalfa

Bouldin Corn

East End

East Pond / Sherman Wetland Temp Tower (both sites had same set of SRS sensors)

Mayberry

Sherman Wetland

Twitchell Alfalfa / Sherman Barn (both sites had same set of SRS sensors)

 West Pond

 

 

Figure 1. Bouldin Alfalfa data. SRS sensor here did not seem to decay over the last few years. The general trends of NDVI from the SRS, Arable, and Apogee sensors match well, although the peak NDVI from Arable, Apogee, and PL data are all around 0.8, whereas the peak NDVI from the SRS sensors is around 0.7. higher than the SRS data. The Arable data seems noisier than the others in late 2020.

 

Figure 2. Linear regression of BA data. The SRS and Apogee sensors are a tight fit with R2=0.98. There is more noise in the Arable and PL regressions with R2=0.74 and R2=0.81, respectively.

 

Figure 3. Incoming Red bands from SRS, Apogee, and Arable sensors. Values match well, although Arable data is a little lower.

 

Figure 4. Incoming NIR bands from SRS, Apogee, and Arable sensors. Values match well, although again Arable data is a little lower. 

 

Figure 5. Outgoing Red bands from SRS, Apogee, and Arable sensors. SRS values are higher than Apogee and Arable.

 

Figure 6. Outgoing NIR bands from SRS, Apogee, and Arable sensors. Apogee and SRS data match, but Arable values are a little lower.

 

Figure 7. Red reflectance from SRS, Apogee, Arable, and PL data. SRS values are higher, but overall trends match.

 

Figure 8. NIR reflectance from SRS, Apogee, Arable, and PL data. Overall trends match, but Arable values are a little lower.

 

 

 

Figure 9. Linear regression of NDVI data against GCC data. The Apogee NDVI has the best fit at R2=0.82, but it also has the last number of points (9 months). Just curious how well the GCC data can predict NDVI.