Abstract
Reference of Earth-observing satellite sensor data to a common, consistent radiometric scale is an increasingly critical issue as more of these sensors are launched; such consistency can be achieved through radiometric cross-calibration of the sensors. A common cross-calibration approach uses a small set of regions of interest (ROIs) in established Pseudo-Invariant Calibration Sites (PICS) mainly located throughout North Africa. The number of available cloud-free coincident scene pairs available for these regions limits the usefulness of this approach; furthermore, the temporal stability of most regions throughout North Africa is not known, and limited hyperspectral information exists for these regions. As a result, it takes more time to construct an appropriate cross-calibration dataset. In a previous work, Shrestha et al. presented an analysis identifying 19 distinct “clusters” of spectrally similar surface cover that are widely distributed across North Africa, with the potential to provide near-daily cloud-free imaging for most sensors. This paper proposes a technique to generate a representative hyperspectral profile for these clusters. The technique was used to generate the profile for the cluster containing the largest number of aggregated pixels. The resulting profile was found to have temporal uncertainties within 5% across all the spectral regions. Overall, this technique shows great potential for generation of representative hyperspectral profiles for any North African cluster, which could allow the use of the entire North Africa Saharan region as an extended PICS (EPICS) dataset for sensor cross-calibration. This should result in the increased temporal resolution of cross-calibration datasets and should help to achieve a cross-calibration quality similar to that of individual PICS in a significantly shorter time interval. It also facilitates the development of an EPICS based absolute calibration model, which can improve the accuracy and consistency in simulating any sensor’s top of atmosphere (TOA) reflectance.
Highlights
Satellite image data have been successfully used to characterize and monitor natural and man-made changes to the Earth’s surface over time
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Summary
Satellite image data have been successfully used to characterize and monitor natural and man-made changes to the Earth’s surface over time. As the use of these sensors increases, a primary concern for researchers is ensuring the data are referenced to a common and consistent radiometric scale [1]. This can be achieved through accurate radiometric calibration of each sensor prior to its launch and at regular intervals after launch throughout its operating lifetime. Many sensor designs include an onboard calibration data source such as lamps or a solar diffuser panel. Various calibration target regions on the Earth’s surface have “ground truth” radiance and/or reflectance measurements available during periods around a sensor overpass, allowing a more direct vicarious calibration approach. An indirect vicarious calibration approach involves cross-calibration between multiple sensors based on analysis of cloud-free coincident or near-coincident image pairs
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