Actually I take that back, using extract() with `weights=TRUE` returned
`0` instead of NA values for these problematic coastal admin units.
Think I might have to impute them manually.
On 10/18/2016 2:33 PM, Bacou, Melanie wrote:
> Thanks, using `weights=TRUE` to compute the means fixed the problem.
> Perfect, --Mel.
> On 10/18/2016 11:10 AM, chris english wrote:
>> Looking at detail in cjg.png the northmost missing data island shows
>> approx 20-25 in Southern three quarters and 0-5 the small North at
>> tip of island. Directly above this 0-5 another coastal 0-5.
>> If a substantial east-west scarp bisected the island it might
>> explain. I would otherwise expect a very slight mismatch in
>> projection, a thing I often have problems with.
>> Though reading raster::extract it looks like you want to employ the
>> weights are if your polys are relatively smaller than your cells.
>> On Oct 18, 2016 4:35 PM, "Bacou, Melanie" <m...@mbacou.com
>> <mailto:m...@mbacou.com>> wrote:
>> I'm summarizing biophysical rasters (UDEL precipitation and
>> temperature) across administrative units for countries in Africa
>> using (pseudo code):
>> raster::extract(udel, admin, fun=mean, na.rm=T, small=T)
>> Out of the 756 units I need data for, extract() fails to return
>> means for a few coastal units (in red on the maps below) even
>> though the rasters show data at these locations.
>> Is there a particular reason why this might happen? Shall I look
>> for possible geometry errors in my source shapefiles, or could
>> there be another reason?
>> Maps here:
>> Thanks for any tip. --Mel.
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