Public transit system plays the central role for traveling in cities of China. Therefore, it is important to study the accessibility provided by public transit. However, public transit influences accessibility in unique ways, which depends significantly on the routes, schedule, location of the users as well as the time of day the trip is made. Existing researches scarcely establish high-resolution spatio-temporal models, calculate travel time accurately, consider the time constraint, or achieve large-scale accessibility analysis. This paper establishes a high-resolution spatio-temporal model based on road network, bus network, metro network and schedule information, designs an efficient time-dependent transfer algorithm combining Hub with A^* Algorithm. To demonstrate the reliability of the model and the efficiency of the algorithm, a case study is presented with respect to mapping accessibility of public transit in Wuhan.