You’ve used Surfer to grid your data and created a great looking map. You put it in the final report for your presentation. And you think, that was easy and I’m all done now.
The final map is prepared and ready for the report.
And then someone asks you, how do you know that map is accurate? You start to wonder. How do I know if it is correct? Is there any way to verify the gridding? If the grid file matches the original data, then I could confidently say the map is correct. But, how do I know if the grid file matches the data?
There are a few ways to determine if a grid file matches the data. You can visually inspect the grid, comparing Z values to known points on map. If you want a more numerical analysis, you can calculate the residual value difference between the grid and the data by clicking the Grid | Residual command. This numerical method will be discussed in another blog later this week.
Visually looking at the difference between the grid and the data is a quick check. To visually inspect the grid, overlay a contour map from the grid with a classed post map from the original data.
To do this:
Note the minimum, maximum, and contour interval.
These will be used later to determine the number
of classes for the classed post map.
The contour map is used to visually see where the Z values are mapped in the grid.
Visually compare the original data points and the contour
lines to get an idea of how the grid represents the data.
Visually, you can see that symbols typically fall in the same colored contour areas. This gives a good indication of how well the data is fit by the grid. You can compare specific Z values (or ranges of Z values) between the classed post map and contour map by labeling the classed post points and comparing the values to the color scale object or contour line labels. You can also move the cursor over the location and seeing the Z value of the contours at that point in the status bar. So, now you can say with confidence that the grid looks to be a good representation of the data.
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