The rapid development of new technologies has presented both opportunities and challenges for planners. On one hand, advanced technologies have presented planning professions tools which may be used to:
engage the public in critical decision-making processes;
analyze and present information in innovative and important ways;
utilize information in the assessment of future planning scenarios;
On the other hand, the rapid rise of advanced technologies has altered many societal norms. The incredible growth in communications technologies, for example, has had tremendous impacts on the theory of business locations. The importance of physical proximity is being diminshed by the ability to serve and supply customers in real time from remote locations where operational cost savings may be realized.
The papers which follow explore these two themes: the application of new technologies to the planning process and the implications of changing technology on planning vibrant communities.
R. D. Feick and B. Boots, 2005. Variable Resolution Spatial Interpolation Using the Simple Recursive Point Voronoi Diagram, Geographical Analysis 37, 225–243. 
Spatial data consist of measurements (data values) of an attribute taken at specific locations (data sites) in a geographic space (study region). In much of the data collected in the environmental sciences, the attribute is assumed to be spatially continuous (possibly piecewise) so that the data values can be considered as a sampling of the attribute at the data sites. Suppose that our primary aim is to use the data to interpolate the values of the attribute at locations other than the data sites, thus enabling us to create a visual representation of the underlying surface. This task can be considered as a specific instance of the more general problem of approximating surfaces that arises in a variety of applications in computer-aided design, computer graphics, computer vision, and finite element methods. In many situations, the data sites are sparse and there is no possibility (due to cost of feasibility) of supplementing their number by increasing the size of the sample. We propose a procedure for progressively increasing the density of an initial point set that provides a basis for interpolating surfaces of variable resolution from sparse samples of data sites. The procedure makes use of the simple recursive point Voronoi diagram (SRPVD).
