Neighborhood relation diagrams for local comparison of carbon footprints in urban planning

Abstract

The dreaded effects of climate change have led to a new research focus in many applications. In urban planning, the visualization of carbon footprints has become one of the most sought after aspects. Urban planning data of carbon footprints contains spatial (location) and abstract (statistical indicators) information. Although many techniques for the visualization of such partially spatial data have been successfully applied in the area of geovisualization, the core focus has been on a global depiction of non-spatial information. However, conducting local comparisons, as in the case of comparing neighborhood districts and households, is of particular importance in investigative tasks. Additionally, representing different carbon footprint indicators (multiple non-spatial parameters) and unstructured parameter values (resulting in scaling issues) in a static representation provides an interesting challenge for visualization. This paper describes a novel and generic solution to the above-mentioned issues: a neighborhood relation diagram for the local comparison of non-spatial information in partial spatial data. The technique is based on the geometric computation of Voronoi diagrams according to a weighted neighborhood metric. The shape of spatial regions (e.g. city districts) within this diagram is characterized by a directed and constrained deformation according to the non-spatial (i.e. carbon footprint) relations to neighboring regions. The effectiveness of our method is highlighted in a preliminary study of carbon footprint patterns in downtown Phoenix (Arizona, USA). In this study, neighborhood relation diagrams enable city planners to detect local effects on carbon emissions and their relation to planning projects.