Normalization of Pseudo-invariant Calibration Sites for Increasing the Temporal Resolution and Long-Term Trending

Given their low level of temporal, spatial, and spectral variability, Pseudo-Invariant Calibration Sites (PICS) have been increasingly desired as data sources for radiometric calibration of Earth imaging satellite sensors. The temporal resolution for PICS data acquired by any sensor is limited by the amount of time required for it to make subsequent passes over the site. Consequently, for any given PICS, it can take many years of imaging to develop a sufficient amount of cloud-free data to perform radiometric calibration; this can be especially problematic for sensors in their early years after launch. This thesis presents techniques to combine Landsat-8; normally acquiring data for every 16 days, image data from multiple PICS into a single dataset with increased temporal resolution and is called “PICS Normalization Process” or PNP. Landsat-8 Operational Land Imager (OLI) data from six Saharan desert sites were normalized to the Libya-4 reference. The normalized data were then merged into a “Super PICS” dataset, and the estimation of calibration drift was derived. The results of the Super PICS dataset show that the temporal resolution of the calibration dataset can be increased by approximately a factor of three to four times. The normalization process was performed on radiometrically and geometrically corrected image data (“L1T” product), and also on the same image data corrected for BRDF effects using a quadratic function of the solar zenith angle and TOA reflectance over a region of interest. An additional uncertainty analysis was performed using the BRDF corrected image data based on the following parameters which are involved in this whole BRDF PICS Normalization Process: Worst-case histogram bin analysis, Temporal Uncertainty of each PICS, BRDF Super PICS uncertainty. The resulting uncertainties are within the currently accepted satellite calibration range, within 3% for all spectral bands. Overall, the process indicates a calibration drift for OLI within 0.15% per year, agreeing quite well with the calibration drift derived from the on-board calibrators

Improved Temporal Resolution of Pseudo Invariant Calibration Sites (PICS) Through Development of the PICS Normalization Process (PNP)

PICS (Pseudo Invariant Calibration Sites) have been used for on-orbit radiometric trending of optical satellite sensors for many years. It takes advantage of the properties of PICS which is highly invariant, any trend in the data would indicate a change in sensor responsivity rather than a change in the apparent reflectance of the target/atmosphere system. However, the length of time that is required to determine a change in sensor responsivity is measured by the drift estimates using a function of the residual noise in the PICS target/atmosphere system and the number of days between imaging opportunities with the sensor being calibrated. Often this can require several years of imaging PICS, using only cloud free data, to detect a small change in sensor responsivity. Six primary Saharan PICS locations were selected according to their level of temporal/spatial stability. Each of these sites was normalized to the well-known Libya- 4 PICS which is used as the overall reference calibration site. Pseudo Invariant Calibration sites (PICS) Normalization process (PNP) is a technique developed to combine sensor observations of multiple PICS into a single time series with greater temporal resolution for satellite calibration. As a result, the temporal resolution using this method can theoretically be improved by a factor of four. This PNP technique was applied to Landsat-8 data to determine if small changes in sensor responsivity can be detected in a shorter time period than when only one PICS is utilized in the trending process. It was found that the PNP, using almost 4 years of image observations over 6 primary PICS, can give a sensor trending estimates to within 0.50 % per year for all VNIR and SWIR bands. Index Terms— PICS, PNP, calibration, trending, Landsat-

PICS Normalization: Improved Temporal Trending Using PICS

Pseudo Invariant Calibration sites (PICS) have been used as a method of vicarious calibration of optical remote sensing satellites since the turn of the century. The broadest application comes from trending satellite responsivity and cross-calibration of satellites, although some have suggested that absolute radiometric calibration using PICS is also possible. Trending of satellite responsivity is done simply by imaging a PICS with the satellite sensor as often as possible over a period of time. If the PICS is truly invariant, then any trend in the data would indicate a change in sensor responsivity rather than a change in the apparent reflectance of the target/atmosphere system. However, the length of time that is required to determine a change in sensor responsivity is a function of the residual noise in the PICS target/atmosphere system and the number of days between imaging opportunities with the sensor being calibrated. Often this can require several years of imaging PICS to detect a small change in sensor responsivity. This paper presents an augmented PICS calibration approach that seeks to combine sensor observations of multiple PICS into a single time series with greater temporal resolution. Six primary Saharan PICS locations were identified according to their level of temporal/spatial stability. Each of these sites was normalized to the well-known Libya 4 PICS which is used as the overall reference calibration site. As a result, the temporal resolution using this method can theoretically be improved by a factor of six. This technique was applied to Landsat data to determine if small changes in sensor responsivity can be detector in a shorter time period than when only one PICS is utilized in the trending process. Results showing the effect of greater temporal resolution on PICS trending precision will be presented