<div dir="ltr"><div><div>Hi Mark:<br><br></div>I think that "point sampling tool" plugin is the tool what you need, With it, you take the corresponding raster value into the points attribute table, so in a new column you can calculate difference between point value and sampled value and make a statistic analysis of that difference.<br>
<br></div><div></div>Good luck<br><br>Carlos Cerdán<br></div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-08-12 13:35 GMT-05:00 Mark Coletti <span dir="ltr"><<a href="mailto:mcoletti@gmail.com" target="_blank">mcoletti@gmail.com</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">I have two sets of vaguely coincident point data that I'd like to compare. Each point has a corresponding measure, and I'd like to assess the spatial similarity between these two sets of measurements. My approach would be to convert these values into grid data and then use techniques for comparing the similarity of matrices.<div>
<br></div><div>Since I'm new to using qgis in an analytical fashion I'm uncertain of the best way of implementing this scheme. For one thing, there appear to be a number of different means of converting point data into grids/matrices/raster data -- e.g., heatmaps or grid interpolation-- and I have the additional constraints of ensuring that the corresponding MBRs and grid cell sizes are identical for fair comparison.</div>
<div><br></div><div>What would be the best way to do this in qgis? (And, alas, I'm not entirely sure by what I mean by "best". Easiest to do? Less error prone?)<br clear="all"><div><br></div><div>Cheers!</div>
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<div><br></div><div>Mark</div>-- <br><a href="mailto:mcoletti@gmail.com" target="_blank">mcoletti@gmail.com</a><br><div><br></div>
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