I have about 500,000 points collected in a linear grid pattern over a 1 km2 area. The points were collected as part of a metal detection survey. Each point has X,Y and Coil Response mV (min -675.38 max 6104.25) values.
What type of interpolation should be used to visualize the results?
Answer
Your figures show that the point-to-point spacing is about 1 meter. That likely could be close to or less than the resolution (especially if you're penetrating significantly below depth). Thus, almost any form of interpolation will work fine and your task is to minimize the effort. If the data are truly regularly spaced, then a good fast way is to format the data as an ASCII grid export file and open it in your GIS: the software will automatically interpolate in order to display or resample the data. (In ArcGIS you can choose among three methods--nearest neighbor, bilinear, and cubic convolution--with the latter two giving smooth interpolation.) A slower but almost as simple way is to open the data as a point layer, align a grid specification with the layer's extent and spacing so that each point falls into a single cell, and convert the data to raster format. (You might have to rotate the coordinate system to achieve a good alignment, though.) The slowest (and probably most unsatisfactory) methods will be any of the GIS's interpolate-to-raster methods, such as inverse distance, natural neighbor, Voronoi polygon, or--God forbid--any form of Kriging (listed approximately in increasing order of computation time and your effort). If your spacing is a bit irregular, choose a fast method. If you can control the inverse distance parameter, choose as small a value as you are able in order to avoid peak-like artifacts.
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