Degrading data (on purpose)

Question

Hi all, 
    I am trying to do an uncertainty analysis for some bathymetric survey data. We have both single-beam and multi-beam bathymetry, and I am looking to thin down the points brought in from an .xyz file from 0.25 m, to 5 m, to 10 m, etc. Basically, I am looking to plot divergence from point density. So, I have been playing around, and am not finding what seems like should be a fairly simple operation. Basically, I want to take mean values of a group of points (spaced about 25 cm) within a 5x5 m cell (for about 150 cells, created as polygons with a fishnet), and so on and so forth, for about 80 survey sites for both survey types. 
    What I have for my test site is the raw survey data as a feature class (I used a Python script that imports a folder full of .xyz files, and outputs them as point feature classes in a file geodatabase), a fishnet of 5x5 m polygons clipped to the survey extent, and a feature-to-point layer, where a point is created in the center of each polygon. I am thinking that there should be some way to populate the z-value field that I added to the feature-to-point layer with the mean value of the raw points within each polygon.
Any ideas?
Thanks a bunch,
Rob

markdenil · Answer

The term to use, I submit, is 'generalizing', rather than 'degrading'....

RobertRoss2 · Answer

Hi Richard,
  Thanks for the reply. I was trying a spatial join earlier, but was just doing it between the centroid points and the raw data. Doing the two-step with the polygons and then the centroid might be the way to go. I will let you know how it works out.
Thanks,
Rob

RichardFairhurst · Answer

Hi all, 
    I am trying to do an uncertainty analysis for some bathymetric survey data. We have both single-beam and multi-beam bathymetry, and I am looking to thin down the points brought in from an .xyz file from 0.25 m, to 5 m, to 10 m, etc. Basically, I am looking to plot divergence from point density. So, I have been playing around, and am not finding what seems like should be a fairly simple operation. Basically, I want to take mean values of a group of points (spaced about 25 cm) within a 5x5 m cell (for about 150 cells, created as polygons with a fishnet), and so on and so forth, for about 80 survey sites for both survey types. 
    What I have for my test site is the raw survey data as a feature class (I used a Python script that imports a folder full of .xyz files, and outputs them as point feature classes in a file geodatabase), a fishnet of 5x5 m polygons clipped to the survey extent, and a feature-to-point layer, where a point is created in the center of each polygon. I am thinking that there should be some way to populate the z-value field that I added to the feature-to-point layer with the mean value of the raw points within each polygon.
Any ideas?
Thanks a bunch,
Rob

Not sure I followed all of that, but the Spatial Join tool seems like it can create a feature class that would have the IDs of both the points and the polygons.  Then you can summarize the points on the polygon ID.  If a second spatial join is needed to have the points in the center of the Polygon know about the polygon IDs then to that so you can join your summary data to the centroid points. (Or backward if needed as long as you are working with one to one or many to one joins).