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• W2804572497 abstract "The statistical analysis of surface roughness has been applied based on the roughness parameters calculated by the algorithms in spatial domain (SDAs). The morphological surface roughness (MSR), one of the SDAs based on the mathematical morphology, has been succeeded in mapping the lunar topographic roughness at multiscales. However, some typical roughness characteristics, such as the small sharp rock distribution and the inner irregular materials of craters, cannot be indicated on the multiscale MSR maps. In this paper, we improve the MSR method by utilizing the Fourier power spectra (FPS), which is applied to characterize these typical topographic variations by transforming them into their frequency forms. A synthesized parameter called improved morphological roughness (IMR) is designed for quantifying multiscale roughness based on the MSR and FPS values. Compared with the other methods (MSR, root mean square, multiscale morphological roughness, Fourier roughness, and kurtosis), IMR identifies more complicated roughness characteristics on the roughness map based on the Lunar Orbiter Laser Altimeter-derived digital elevation models (DEMs). For the multiscale analysis of different roughness maps, IMR can provide a stable scale-dependent distribution for the classifications of different terrains." @default.
• W2804572497 created "2018-06-01" @default.
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• W2804572497 creator A5090316208 @default.
• W2804572497 date "2018-07-01" @default.
• W2804572497 modified "2023-10-09" @default.
• W2804572497 title "Improved Multiscale Roughness Algorithm for Lunar Surface" @default.
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• W2804572497 doi "https://doi.org/10.1109/jstars.2018.2822297" @default.
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