What to do when raster cell size is larger than zonal vector feature in order to collect statistics?

Question

I am trying to extract the mean cell values for a raster dataset based on a survey grid polygon feature using ArcINFO 10.1. The cell size of the raster dataset is about 4 times the size of the survey grid.

I am working with the FCLIM climate trend analysis data for equatorial Africa (ftp://www.earlywarning.usgs.gov/fews/pubs/mapping_decadal_variations.pdf)

I want the mean value of raster cells/pixels within each polygon grid cell:

I have around 3000 grid cells, using 'zonal statistics as table' tool I get only around 600 results evenly spread about the survey grid. Obviously not the result I am seeking.

When I use the 'zonal statistics' tool the result I get the following raster:

2 things have gone wrong with this output (that may not be immediately evident in the image): the cell size of the output raster is still about 4X larger than the feature zone, survey grid polygons; and secondly the raster cells are not coincident with the feature zone survey grid polygons and indeed no longer coincident with the original raster dataset from which it was derived!

My question is: How can I calculate the mean value of raster cells/pixels residing within the smaller survey polygon grids? Is it a matter of using a different method of breaking up the raster cells or is there another method I should try?

Answer 1

what I would recommend is to avoid zonal statistics when your zones are smaller than the pixel size, especially in your case where you have a regular grid. Instead, you should get the centroids of your polygons, then use the extract multiple value to point. There is an option for the interpolation.

Answer 2

This is explained in the Zonal Statistics help:

If the zone input is a feature dataset with relatively small features, keep in mind that the resolution of the information needs to be appropriate relative to the resolution of the value raster. If the areas of single features are similar to or smaller than the area of single cells in the value raster, in the feature-to-raster conversion some of these zones may not be represented.

If you have fewer results in the output than you may have expected, you need to determine an appropriate raster resolution that will represent the detail of your feature input, and use this resolution as the Cell Size of the Raster Analysis Settings of the Environment.

Based on that information, I would do the following:

1. Make sure both rasters are in the same projected coordinate system if they aren't already.
2. Use the Resample geoprocessing tool to reduce the cell size of your climate data to a size less than or equal to your zones. For the resampling_type parameter, I would suggest using BILINEAR or CUBIC since your data are continuous; this will interpolate cell values to create a smoother surface.
3. Run Zonal Statistics using your projected and resampled data.

Alternatively, you can adjust the Cell Size environment variable to control how Spatial Analyst conducts its internal resampling of layers. However, I prefer to be able to see the resampled data as output from the Resample tool for QA/QC of the Zonal Stats raster.