HS
H.J. Sletsjøe
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This thesis investigates terrain ruggedness characterization based on low-order terrain statistics. The statistics in question are the root-mean-square height and slope where the slopes are calculated both directly using the power spectral density and indirectly via a finite difference scheme. These statistics are, in contrast to the ruggedness index, shown to be close to independent of the input map resolution making them more suitable for future use due to the increased availability of high quality maps. Furthermore, these metric scan be bridged to the ruggedness index through strong correlations, thereby making implementation much simpler. The low-order statistics provide a strong, future-proof alternative to the current terrain ruggedness index and early investigations in this report have shown promise in the development of sector-wise correlations. Such correlations could yield directional correction factors as opposed to the current omnidirectional ∆RIX correction factor.
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This thesis investigates terrain ruggedness characterization based on low-order terrain statistics. The statistics in question are the root-mean-square height and slope where the slopes are calculated both directly using the power spectral density and indirectly via a finite difference scheme. These statistics are, in contrast to the ruggedness index, shown to be close to independent of the input map resolution making them more suitable for future use due to the increased availability of high quality maps. Furthermore, these metric scan be bridged to the ruggedness index through strong correlations, thereby making implementation much simpler. The low-order statistics provide a strong, future-proof alternative to the current terrain ruggedness index and early investigations in this report have shown promise in the development of sector-wise correlations. Such correlations could yield directional correction factors as opposed to the current omnidirectional ∆RIX correction factor.