<html style="direction: ltr;">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<style type="text/css">body p { margin-bottom: 0cm; margin-top: 0pt; } </style>
</head>
<body bidimailui-charset-is-forced="true" style="direction: ltr;"
text="#000000" bgcolor="#FFFFFF">
Hi Rich<br>
<br>
<br>
<div class="moz-cite-prefix">On 09/24/2018 06:32 PM, Rich Shepard
wrote:<br>
</div>
<blockquote type="cite"
cite="mid:alpine.LNX.2.20.1809240832080.20499@salmo.appl-ecosys.com">
I want to determine whether GRASS or R is best suited to
<br>
interpolating/extrapolating annual mean precipitation data from 58
reporting
<br>
stations (unevenly distributed within the county) across the
county. Some
<br>
flavor of kriging would be applied to these data to illustrate a
general
<br>
long-term pattern of rainfall.
<br>
<br>
Some years ago there was both a static display of a chemical
constituent
<br>
in a river reach, a "heat map", (and an automation of temporal
changes, if I
<br>
correctly recall) and I'm not finding this in the web site
galleries.
<br>
<br>
While elevation could be included as an explanatory variable
using
<br>
regression kriging my purpose is to illustrate county-wide mean
annual rainfall
<br>
distribution over a 13 year period, not to interpolate values for
specific,
<br>
unsampled locations.
<br>
<br>
Please provide some thoughts on the work flow to do this within
GRASS. I'm
<br>
digging into the gstat docs to get a sense of how to do this
within R (and I
<br>
have the rgrass7 package working well; it imported the GRASS
county boundary
<br>
map which I converted to a SpatialPolygonDataFrame.)
<br>
<br>
</blockquote>
<br>
The guidelines that I follow include: <br>
<ul>
<li>Rainfall interpolation (of any kind) should be done only for
long time periods = at least a full season. since you are
looking at 13 years of data then this requirement is fulfilled.</li>
<li>The rules of thumb for "how many points" for kriging
interpolation usually says > 30. So again you are fine.</li>
<li>The GRASS modules offer only ordinary kriging AFAIK, which
might be appropriate in this case. But if you want to use
Kriging with External Drift with the elevation as the secondary
"trend" variable, I think you'll need to go with with R. Having
said that, I think that "the jury is still out" on whether
elevation improves the interpolation or not. </li>
</ul>
Regards, Micha<br>
<blockquote type="cite"
cite="mid:alpine.LNX.2.20.1809240832080.20499@salmo.appl-ecosys.com">Rich
<br>
<br>
_______________________________________________
<br>
grass-user mailing list
<br>
<a class="moz-txt-link-abbreviated" href="mailto:grass-user@lists.osgeo.org">grass-user@lists.osgeo.org</a>
<br>
<a class="moz-txt-link-freetext" href="https://lists.osgeo.org/mailman/listinfo/grass-user">https://lists.osgeo.org/mailman/listinfo/grass-user</a><br>
</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Micha Silver
Ben Gurion Univ.
Sde Boker, Remote Sensing Lab
cell: +972-523-665918</pre>
</body>
</html>