Extended Pseudo Invariant Calibration Site-Based Trend-to-Trend Cross-Calibration of Optical Satellite Sensors

Abstract

Satellite sensors have been extremely useful and are in massive demand in the understanding of the Earth’s surface and monitoring of changes. For quantitative analysis and acquiring consistent measurements, absolute radiometric calibration is necessary. The most common vicarious approach of radiometric calibration is cross-calibration, which helps to tie all the sensors to a common radiometric scale for consistent measurement. One of the traditional methods of cross-calibration is performed using temporally and spectrally stable pseudo-invariant calibration sites (PICS). This technique is limited by adequate cloud-free acquisitions for cross-calibration which would require a longer time to study the differences in sensor measurements. To address the limitation of traditional PICS-based approaches and to increase the cross-calibration opportunity for quickly achieving high-quality results, the approach presented here is based on using extended pseudo invariant calibration sites (EPICS) over North Africa. With the EPICS-based approach, the area of extent of the cross-calibration site covers a large portion of the North African continent. With targets this large, many sensors should image some portion of EPICS nearlydaily, allowing for evaluation of performance with much greater frequency. By using these near-daily measurements, trends of the sensor’s performance are then used to evaluate sensor-to-sensor daily cross-calibration. With the use of the proposed methodology, the dataset for cross-calibration is increased by an order of magnitude compared to traditional approaches, resulting in the differences between any two sensors being detected within a much shorter time. Using this new trend in trend cross-calibration approaches, gains were evaluated for Landsat 7/8 and Sentinel 2A/B, with the results showing that the sensors are calibrated within 2.5% (within less than 8% uncertainty) or better for all sensor pairs, which is consistent with what the traditional PICS-based approach detects. The proposed cross-calibration technique is useful to cross-calibrate any two sensors without the requirement of any coincident or near-coincident scene pairs, while still achieving results similar to traditional approaches in a short time.