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<p lang="zxx">Hi PDALers,</p><p lang="zxx">I continue investigation into aerial lidar
classification prediction. I'm interested in calculating metrics
over a known local volume for each point. The specific examples I'm
considering:<br></p>
<p lang="zxx">- Normals. Filters.normal allow us to specify how many
nearest neighbors go into the calculation but without consideration to
how far away they are. Does does it make sense to specify a radius
in addition to the number of neighbors? So, perhaps calculate
normals based on all points at most 3 meters away:</p>
<p lang="zxx"> {</p>
<p lang="zxx"> "type":"filters.normal",</p>
<p lang="zxx"> "radius":3</p>
<p lang="zxx"> }</p>
<p lang="zxx">- Normal variance. HeightAboveGround variance. Along
the same lines, I'd like to augument each point with the magnitude
of local normal-variance and local HAG-variance. Perhaps</p>
<p lang="zxx"> {</p>
<p lang="zxx"> "type":"filters:variance",</p>
<p lang="zxx"> "radius":3,</p>
<p lang="zxx"> "dimensions":"NormalX, NormalY,
NormalZ, HeightAboveGround"</p>
<p lang="zxx"> }</p>
<p lang="zxx"><br>
<br>
</p>
<p lang="zxx">Does anyone have thoughts on how to proceed?
</p>
<p lang="zxx" style="margin-bottom:0in"><br>
</p></div>