hrynykd

Gridding unevenly sampled categorical data

Discussion created by hrynykd on Sep 12, 2011
Latest reply on Sep 20, 2011 by lpinner
Hello,

I was a long-time participant on ESRI-L and ArcView-L but, this is my first post to the new forums.  I hope I have posted this query in the most appropriate forum.  If there is a better choice, please let me know.

I am looking for a method for gridding categorical data.  I have extracted from nautical charts and field sheets a collection of points specifying the nature of the surface of the bottom of the ocean.  These data are categorical rather than numerical and they are not regularly nor even randomly sampled.  Nautical charts are created to aid in navigation and anchoring;  they are not created to map habitat.  As such, more soundings are made close to shore where relatively shallow depths can pose a hazard to navigation and where ships to tend to anchor.  Further from shore,  where the depths are more than adequate for navigation and anchoring is impractical, soundings are made much less frequently.

Has anyone else tried to create gridded substrate maps from nautical charts?

I looked at Theissen (Vornoi) polygons but the concentration of soundings along shores leads to a fine 'honeycomb' along the shore, large polygons offshore and in between long pie-shaped polygons stretching way offshore.  Gridding using nearest neighbour yields pretty much the same result.

I need a way to limit the influence of the shallow, near shore points -- a way to limit those long pie-shaped polygons.  In deeper waters I do not expect that the nature of the bottom will be a continuation of the near shore bottom.  I have been thinking along two lines -- both using depth.  One is weighting the choice of the 'nearest' neighbour using the difference in depth between a grid cell and neighbouring points.  Another is de-selecting neighbouring points which are more than some specified tolerance different in depth.  Or, perhaps rather than a pre-specified tolerance, I could bin depth ranges and then limit the choice of neighbouring points to those in the same depth range or bin.

Any thoughts on how to implement either of these two options?

Can any one suggest other lines to follow?  (One could, perhaps, use terrain analysis.  For example, slopes steeper than the angle of repose could not be sediments.  I am looking for something simpler and, at any rate, I do not have data at sufficient spatial resolution.)

Regards,


Doug Hrynyk

Outcomes