Hello Kim,
I believe the most efficient way to do this would be to convert the raster to points and perform a spatial join between the points and the polygon shapefile.
To address for your 'no data' values in your raster, after converting the raster to points, you can start an edit session, perform a selection by attribute to select all 'null' valued points then delete your selection.
Saving your edits and then performing your spatial join will then only use points with values to calculate your statistics (which in this case, you would select MEAN).
Hope this helps!
Best,
Chris B.
Okay that's what I thought. It is not appropriate to interpolate the raster values �??�??within polygons then, somehow? Or use some density analysis? Or block statistics?
Interpolation will estimate values between known values.
Density will only account for the number of values within a given area.
Block statistics will not use your polygons (unless you create a kernel file for an irregular neighborhood which would take a great deal of time) to calculate your statistic.
Although it may sound cumbersome, the process I outlined earlier is pretty straightforward and only requires three steps:
1. Convert raster to points
2. Select/delete null values
3. Spatial join points to polygons
Okay, but can I get mean then? It might on the other hand not be very hard to calculate this with the field calculator for each polygon?
What I mean with null values �??�??is that not all of the polygon covered by the grid. I might not have to deal with these at all then because they represent water surfaces, built up areas, etc..