The accelerating urbanization procedure is putting increasing pressure on the management of cities. The administrative zones by which a city is managed are setup based on historical or political reasons, while the dynamics of people is hardly considered in the context. We exploit the widely available mobility data to divide the urban areas into zones by the joint K-mean clustering in origin and destination spaces. The method is evaluated with the New York City and Shenzhen taxi data, and the created zones are compared with the current static zoning plans of the city to evaluate the effectiveness.