Abstract
Pseudo invariant calibration sites (PICS) have been extensively used for the radiometric calibration and temporal stability monitoring of optical satellite sensors. Due to limited knowledge about the radiometric stability of North Africa, only a limited number of sites in the region are used for this purpose. This work presents an automated approach to classify North Africa for its potential use as an extended PICS (EPICS) covering vast portions of the continent. An unsupervised classification algorithm identified 19 “clusters” representing distinct land surface types was used; three clusters were identified with spatial uncertainties within approximately 5% in the shorter wavelength bands and 3% in the longer wavelength bands. A key advantage of the cluster approach is that large numbers of pixels are aggregated into contiguous homogeneous regions sufficiently distributed across the continent to allow multiple imaging opportunities per day, as opposed to imaging a typical PICS once during the sensor’s revisit period. This potential increase in temporal resolution could result in increased sensitivity for the quicker identification of changes in sensor response.
Funder
National Aeronautics and Space Administration
U.S. Geological Survey
Subject
General Earth and Planetary Sciences
Cited by
22 articles.
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