Supervised Vicarious Calibration (SVC) of Multi-Source Hyperspectral Remote-Sensing Data
AbstractIntroduced in 2011, the supervised vicarious calibration (SVC) approach is a promising approach to radiometric calibration and atmospheric correction of airborne hyperspectral (HRS) data. This paper presents a comprehensive study by which the SVC method has been systematically examined and a complete protocol for its practical execution has been established—along with possible limitations encountered during the campaign. The technique was applied to multi-sourced HRS data in order to: (1) verify the at-sensor radiometric calibration and (2) obtain radiometric and atmospheric correction coefficients. Spanning two select study sites along the southeast coast of France, data were collected simultaneously by three airborne sensors (AisaDUAL, AHS and CASI-1500i) aboard two aircrafts (CASA of National Institute for Aerospace Technology INTA ES and DORNIER 228 of NERC-ARSF Centre UK). The SVC ground calibration site was assembled along sand dunes near Montpellier and the thematic data were acquired from other areas in the south of France (Salon-de-Provence, Marseille, Avignon and Montpellier) on 28 October 2010 between 12:00 and 16:00 UTC. The results of this study confirm that the SVC method enables reliable inspection and, if necessary, in-situ fine radiometric recalibration of airborne hyperspectral data. Independent of sensor or platform quality, the SVC approach allows users to improve at-sensor data to obtain more accurate physical units and subsequently improved reflectance information. Flight direction was found to be important, whereas the flight altitude posed very low impact. The numerous rules and major outcomes of this experiment enable a new standard of atmospherically corrected data based on better radiometric output. Future research should examine the potential of SVC to be applied to super-and-hyperspectral data obtained from on-orbit sensors. View Full-Text
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Brook, A.; Ben-Dor, E. Supervised Vicarious Calibration (SVC) of Multi-Source Hyperspectral Remote-Sensing Data. Remote Sens. 2015, 7, 6196-6223.
Brook A, Ben-Dor E. Supervised Vicarious Calibration (SVC) of Multi-Source Hyperspectral Remote-Sensing Data. Remote Sensing. 2015; 7(5):6196-6223.Chicago/Turabian Style
Brook, Anna; Ben-Dor, Eyal. 2015. "Supervised Vicarious Calibration (SVC) of Multi-Source Hyperspectral Remote-Sensing Data." Remote Sens. 7, no. 5: 6196-6223.