Improving remotely sensed soil moisture estimates requires calibration and validation from ground-based observations obtained from established monitoring networks. Network sites are often installed at the edges of fields (in grass strips), and it is unknown if the soil moisture conditions at the network sites are similar to those observed within the fields. Intensive field campaigns, that include extensive spatial sampling of soil moisture, can be used as a basis for comparison for network sites. This study utilized data from the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10). Regional mean soil moisture (at the scale required for passive microwave remote sensing) obtained from the network sites (32 in total) was compared to the mean soil moisture obtained from field locations (55–60 fields) within the same region for the 6 days of the field campaign. The mean difference between the regional mean network soil moisture and the regional mean field soil moisture was < 0.04 m3 m−3 for each day of the campaign. A bootstrapping technique, which randomly sampled the network data, determined that the regional field mean soil moisture fell within the 95% confidence interval for the network data for all days and resulted in a root mean square error (RMSE) between the network and the regional field soil moisture of < 0.03 m3 m−3. Thiessen polygons were used as an upscaling technique to determine the regional-scale soil moisture resulting from network and manual field measurements. The results indicated that the difference between the regional-scale soil moisture from the network versus the field measurements was < 0.041 m3 m−3 for all sampling days. A Monte Carlo analysis indicated that 25 of the network stations (within a region of approximately 1600 km2) would be required in order for the network mean to be within 0.04 m3 m−3 of the field mean soil moisture with 95% confidence.