Journal of Remote Sensing Technology
Journal of Remote Sensing Technology(JRST)
ISSN:2330-1767(Print)
ISSN:2330-1775(Online)
Frequency: Annually
Website: www.bowenpublishing.com/jrst/
Separability Analysis of Integrated Spaceborne Radar and Optical Data: Sudan Case Study
Abstract:
The purpose of this study was to determine via spectral separability using divergence measures the best individual and combinations of various numbers of bands for five land cover/ land use classes along the Blue Nile in Sudan. The data for this analysis were a stack of 15 layers including RADARSAT-2 C-band and PALSAR L-band quad-polarized radar registered with ASTER optical data, as well as four variance texture measures extracted from the RADARSAT-2 images. Spectral signatures were obtained for each class and examined by various separability measures. This examination is useful for better understanding the relative value of different types of remote sensing data and best band combinations for possible visual analysis and for improving land cover/ land use classification accuracy. Results show that the best single band for analysis was the RADARSAT-2 VH variance texture measure. The best pair of bands was the ASTER visible red and the RADARSAT-2 HV variance texture, which also included the PALSAR VH band for the best three band combination, all bands being very different data types. Further, based upon the divergence values, only eight bands are needed to achieve maximum separation between land cover/ land use classes. Beyond this point, classification accuracy is expected to decrease, with as few as six bands needed to reach viable classification accuracy.
Keywords:Separability; Divergence; RADARSAT-2; PALSAR; ASTER; Quad-polarization; Sensor Integration; Sensor Fusion; Texture; Sudan
Author: Barry Haack,Ron Mahabir

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