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the large central valley and the l atness of the terrain.
h e stream power index is another important secondary relief attribute that
is frequently used in hillslope hydrology, geomorphology, soil science, and
related disciplines. As a measure of stream power it provides an indication
of the potential for sediment transport and erosion by water. It is dei ned as
the product of the catchment area for a specii c cell and the tangent of the
slope of that cell:
h e potential for erosion is high when large quantities of water (calculated by
l ow accumulation) are fast l owing due to an extreme slope. h e following
series of commands compute and display the stream power index:
spi = flowac.*tand(slp);
h = pcolor(log(1+spi));
colormap(jet), colorbar
set(h,'LineStyle','none')
axis equal
title('Stream power index')
[r c] = size(spi);
axis([1 c 1 r])
set(gca,'TickDir','out');
h e wetness and stream power indices are particularly useful in high
resolution terrain analysis, i.e., digital elevation models sampled at intervals
of less than 30 meters. In our terrain analysis example we have calculated
weti and spi from a medium resolution DEM, and must expect a degree of
scale dependency in these attributes.
h is section has illustrated the use of basic tools for analyzing digital
elevation models. A more detailed introduction to digital terrain modeling
is given in the topic by Wilson & Galant (2002). Furthermore, the article
by Freeman (1991) provides a comprehensive summary of digital terrain
analysis, including an introduction to the use of advanced algorithms for
l ow accumulation.
7.11 Geostatistics and Kriging (by R. Gebbers)
Geostatistics describes the autocorrelation of one or more variables in 1D,
2D, or 3D space, or even in 4D space-time, in order to make predictions
for unobserved locations, to obtain information on the accuracy of the
predictions, and to reproduce spatial variability and uncertainty. h e
shape, range, and direction of the spatial autocorrelation are described by
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