Based on automation scale and digitizer precision
The most accurate method for setting the fuzzy tolerance is based on its automation scale and the digitizer precision. This table lists standard automation scales and the corresponding fuzzy tolerance for an industry-standard digitizer precision of 0.002".
| Automation scale of source data | Coverage coordinate units | Fuzzy tolerance (on the ground) at 0.002" digitizer precision |
|---|---|---|
1:200 000 | feet | 33.333 |
meters | 10.130 | |
1:100 000 | feet | 16.620 |
meters | 5.080 | |
1:63 360 | feet | 10.560 |
meters | 3.210 | |
1:25 000 | feet | 4.167 (4.000) |
meters | 1.270 (1.219) | |
1:10 000 | feet | 1.668 |
meters | 0.508 | |
1:5 000 | feet | 0.833 |
meters | 0.254 | |
1:1 000 | feet | 0.167 |
meters | 0.051 | |
1:500 | feet | 0.083 |
meters | 0.025 |
If you don't see the automation scale of your geodataset in the table, calculate the fuzzy tolerance with this equation:
Tolerance in feet = ((automation scale * digitizer precision) / 12)
Tolerance in meters = ((automation scale * digitizer precision) / 12) * 0.3048
Based on geodataset extent
If you don't know the automation scale of the coverage, an alternate method for setting the fuzzy tolerance is based on the coverage extent and uses the coordinate values stored in its BND. This table shows threshold values for various coverage extents:
| Extent | Type of data content | Fuzzy tolerance (resolution) | Divide extent by |
|---|---|---|---|
10 | buildings/streets | 0.001 m | 10 000 |
100 | census block | 0.01 m | 10 000 |
1 000 | census block/tract | 0.1 m | 10 000 |
>1 000 | city tract/town | 0.1 | 0.9 m | 10 000 |
10 000 | city | 1 m | 10 000 |
>10 000 | city/county | 1 m | extent |
100 000 | county | 1 m | 100 000 |
1 000 000 | state/small country | 5 m | 200 000 |
>1 000 000 | continent to globe | 10 m | 1 000 000 |
If you don't see the extent of your geodataset in the table, here's how to calculate the fuzzy tolerance:
- Determine the extent, that is, the larger of (xmax – xmin) and (ymax – ymin).
- Determine a sensible resolution for the type of data content, for example, census block, city, county, state, country, continent, or globe.
- Determine the denominator to get the desired resolution. Use the resolution as the fuzzy tolerance value.
The fuzzy tolerance for double-precision geodatasets is often smaller than that for single-precision coverages, since they are frequently collected from precise sources such as surveying, engineering, and Global Positioning Systems (GPS).