In economic, social, and urban studies, areal units under analysis frequently differ from areal units over which data are compiled. Most area-based analyses, hence, face an unavoidable problem of transferring data across different zonal systems. This paper introduces a novel approach, the overlaid network algorithm, to develop a series of improved methods for tackling the population interpolation problem based on current GIS techniques and available digital information. The term network means that the partitioning of population for source zones is carried out over street segments. People are sheltered by houses which are located along the sides of streets or connected by roads. Thus, the street network provides an important information about the spatial distribution of population. The network length method discerns an even population distribution along one-dimensional line. The network hierarchical weighting method observes variations of residential density among different classes of streets. The network house bearing method breaks the assumptions of even population distribution over one and two dimensions and provides an automatic way of enumerating population over space. The application of these techniques to the interpolation of population in Erie County, New York improves the performance of areal interpolation significantly when compared with traditional methods.