Analysis of synergistic effects of a combined spaceborne multispectral scanner and L-band multiple incidence angle radar data set
Abstract
Three different incidence angle data sets, obtained by the Shuttle Imaging Radar-B in October 1984 over a forested area in northern Florida, were combined with a Landsat-5 Thematic Mapper image, to analyze the effect of incidence angle on radar backscattering and the information content of the data obtained by the two sensors when analyzed simultaneously. The radar data were filtered to eliminate the speckle noise. Classifications of the TM, SIR-B and combined TM+SIR-B data sets were performed with per-point and contextual classifiers. The results indicate that filtered radar data can be used to accurately classify major cover types (such as pine, swamps and radar smooth targets), and that the contextual classifier provides better classification performance. The combined TM and SIR-B data provided statistically significant (at an $\alpha$ level of 0.1) better classification performance as compared to use of only the three SIR-B incidence angle data. A subset of 4 (TM-2, TM-4, TM-5, and SIR-B 28$\sp\circ$) of the available 10 channels of the combined TM and SIR-B data set provided higher classification performances (91% overall performance) than the 10 channel data set (86% overall performance).
Degree
Ph.D.
Advisors
Hoffer, Purdue University.
Subject Area
Forestry|Remote sensing
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