Urban impedance is an important consideration in assessments of transportation and land-use systems. This work leverages check-in records obtained from mobile social networks to build a fine-grained but inexpensive urban impedance model. Check-in records and road networks are collected and used to calculate and adjust the various parameters of the model, including path length, number and angle of turns, number and direction of junctions, and population density. Check-in records can filter functional locations and supply the time factor, thereby providing excellent advantages over traditional models that do not employ this data type. The proposed model is more accurate than traditional impedance models, as verified by experiments using Sina Weibo data in Tianjin City.