Titlebook: MATLAB® Recipes for Earth Sciences; Martin H. Trauth Book 20103rd edition Springer-Verlag Berlin Heidelberg 2010 Kriging.digital elevation

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Introduction to MATLAB,ssachusetts (.). MATLAB was designed to perform mathematical calculations, to analyze and visualize data, and to facilitate the writing of new soft ware programs. The advantage of this soft ware is that it combines comprehensive math and graphics functions with a powerful high-level language. Since

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Univariate Statistics, carbon content of a sedimentary unit, the thickness of a sandstone layer, the age of sanidine crystals in a volcanic ash or the volume of landslides. Both the number and the size of . that we collect from a larger . are oft en limited by financial and logistical constraints. The methods of univaria

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Time-Series Analysis,ds of mountain uplift , sea-level fluctuations, orbitally-induced insolation variations and their influence on the ice-age cycles, millenium-scale variations in the atmosphere-ocean system, the effect of the El Niño/Southern Oscillation on tropical rainfall and sedimentation (Fig. 5.1) and tidal inf

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Signal Processing,s, and to separate out various components of interest. Most signal processing algorithms include the design and realization of filters. A . can be described as a system that transforms signals. . provides the mathematical background for filter design and realization. A filter has an input and an out

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Spatial Data, data are generated by digitizing map objects such as drainage networks or outlines of lithologic units. Raster data can be obtained directly from a satellite sensor output, but gridded data can also, in most cases, be interpolated from irregularly-distributed field samples (gridding)..The following

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Multivariate Statistics,tivariate data sets, such as microfossil assemblages, geochemical fi ngerprints of volcanic ash layers, or clay mineral contents of sedimentary sequences. If there are complex relationships between the diff erent parameters, univariate statistics ignores the information content of the data. There ar

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Statistics on Directional Data,tation of slickensides (or striae) on fault planes. Circular statistics is also common in paleomagnetic applications. Microstructural investigations include the analysis of grain shapes and quartz c-axis orientations in thin sections. Paleoenvironmentalists also reconstruct paleocurrent directions f