# The Ground-Based Absolute Radiometric Calibration of the Landsat 9 Operational Land Imager
## 2 Methodology
### Automated Measurements: The Radiometric Calibration Test Site (RadCaTS)
#### 2.2.6 Surface Reflectance Measurements at the RadCaTS  
One of the primary differences between the RadCaTS and the traditional reflectance-based approach is that of the methodology used to determine the surface BRF. The RadCaTS uses GVRs to measure reflected radiance from the test site surface, while the reflectance-based approach uses the ratio of digital numbers (DNs) collected with a portable spectroradiometer over the ground to those collected over a reference panel [18; 86; 87; 88; 89; 90; 91]. The most notable difference is that the RadCaTS requires a solar exoatmospheric irradiance model to convert the measured reflected surface radiance to a surface BRF [17]. Operationally, the BRF of the RadCaTS ROI is determined for a given time of interest by initially determining the BRF in all eight channels of each GVR. This step requires the spectral radiance measurement in each GVR channel, the atmospheric measurements made by the Cimel sun photometers, the ancillary data (e.g., ambient temperature and pressure), and an exoatmospheric irradiance model. These data are processed in the radiative transfer model (currently MODTRAN 6 [31]), and the output is the multispectral surface BRF, an example of which is shown in Figure 5 for a Landsat 9 overpass on 24 June 2022. The final step in processing the surface reflectance measurements is to convert the multispectral surface BRF to a hyperspectral BRF for use once again in the radiative transfer code. The conversion is completed using a least-squares fit of the multispectral GVR data to one of the hyperspectral data sets in a reference library, which is a collection of portable spectroradiometer measurements made by UArizona personnel over the past thirty years. UArizona personnel are the main source for these data, but more recent BRF data have been obtained from NASA JPL personnel who perform similar measurements for different sensors [92; 48; 93]. A limited amount of snow BRF data have been collected by UArizona personnel during various field campaigns at Railroad Valley, but they are generally not used in RadCaTS or RadCalNet processing. An example of the resulting conversion from  
Figure 5: The retrieved multispectral BRF in each of the eight channels of seven GVRs on 24 June 2022 at 18:20 UTC. Their geolocation at the RadCaTS is shown in Figure 3.  
multispectral to hyperspectral BRF is shown in Figure 6. The procedure to determine the surface BRF for a given date and time is summarized below and also in Figure 7. The equation for the surface BRF determination is shown in Appendix A. 1. Determine the surface BRF in each GVR channel. * Calculate the spectral radiance measured by each GVR channel. * Use a reference monthly average BRF for the diffuse sky irradiance (Esky) calculation. Figure 6: The average multispectral BRF retrieved from the seven GVRs in Figure 5, including the fit to one of the hyperspectral portable spectroradiometer data in the reference library. Figure 7: RadCaTS surface BRF processing. * Obtain the processed AERONET data for the time of interest, including the AOD500 nm, precipitable water vapor (WV) and Angstrom exponent. * Download atmospheric data such as ozone and CO2 amount. * Download ancillary data such as ambient temperature and barometric pressure from the on-site meteorological station at Railroad Valley. * Use the AERONET measurements, the atmospheric data (CO2 and O3), and ambient temperature and pressure data as input into a radiative transfer code. * Convert the multispectral GVR surface BRF to a hyperspectral BRF. * Compute the average surface BRF for each of the eight GVR bands in order to obtain one multispectral surface BRF for the RadCaTS ROI. * Perform a least-squares best fit of the multispectral surface BRF to a library of reference BRF values obtained with multispectral spectroradiometers. * Compare the output hyperspectral surface BRF with the one used in 1b. * If the average difference is higher than a predetermined value, rerun step 1 using the new hyperspectral surface BRF.