I wonder if there is a spatial Nyquist sampling theory?

In article <c3fpl0$rc8$1@mozo.cc.purdue.edu>, walala <mizhael@yahoo.com> wrote:
>I am not sure I understand the concept of spatial frequency.
>For example, we know we have sensor networks now:
>suppose we place sensors into a region to sense temprature. Do we need to
>consider the Spatial Nyquist rate?

Consider an entire county covered with alternating outdoor ice rinks
and bonfires, spaced in a checkerboard grid every 0.2 miles.  If your
temperature sensor network is spaced too widely (say every 0.4 miles),
you might could easily end up with all of the sensors near the bonfires
and measure a completely wrong average temperature for the county.
A little wider spacing, and you might measure the North side of the county
as considerably hotter than the South side due to sample aliasing.  If,
however, your temperature sensor network were spaced every 0.1 miles,
then you would pretty much guarantee measurements near all the bonfires
and the ice rinks and in between and thus more likely to resolve the
temperature frequency (1 peak per 0.4 miles) and get an unaliased
average temperature.


IMHO. YMMV.
-- 
Ron Nicholson   rhn AT nicholson DOT com   http://www.nicholson.com/rhn/ 
#include <canonical.disclaimer>        // only my own opinions, etc.