Validation of Expanded Trend-to-Trend Cross-Calibration Technique and Its Application to Global Scale

The expanded Trend-to-Trend (T2T) cross-calibration technique has the potential to calibrate two sensors in much less time and provides trends on a daily assessment basis. The trend obtained from the expanded technique aids in evaluating the differences between satellite sensors. Therefore, this technique was validated with several trusted cross-calibration techniques to evaluate its accuracy. Initially, the expanded T2T technique was validated with three independent RadCaTS RRV, DIMITRI-PICS, and APICS models, and results show a 1% average difference with other models over all bands. Further, this technique was validated with other SDSU techniques to calibrate the newly launched satellite Landsat 9 with 8, demonstrating good agreement in all bands within 0.5%. This technique was also validated for Terra MODIS and ETM+, showing consistency within 1% for all bands compared to four PICS sites. Additionally, the T2T technique was applied to a global scale using EPICS Global sites. The expanded T2T cross-calibration gain result obtained for Landsat 8 versus Landsat 7/8, Sentinel 2A/2B, and Terra/Aqua MODIS presented that the difference between these pairs was within 0.5-1% for most of the spectral bands. Total uncertainty obtained for these pairs of sensors using Monte Carlo Simulation varies from 2.5-4% for all bands except for SWIR2 bands, which vary up to 5%. The difference between EPICS Global and EPICS North Africa was calculated using the ratio of trend gain; the difference among them was within 0.5-1% difference on average for all the sensors and bands within a 0.5% uncertainty level difference.

Automated summary

The expanded Trend-to-Trend (T2T) cross-calibration technique has been validated with various models and techniques, demonstrating its potential to calibrate sensors efficiently and accurately. The validation results show good agreement and consistency between different sensors and bands, with average differences within 1%. The total uncertainty obtained using Monte Carlo Simulation varies from 2.5-5% for different sensor pairs.