I found it very interesting how Curtin (2007) points out that network analysis is the only subfield of GISciences that has redefined a spatial reference system. Linear referencing, or using the network itself as a reference, is so intuitive that I had never thought of it as an alternative method of spatial referencing. I realize that standardized spatial referencing is something that I take for granted and alternative methods may be an interesting direction for future research.
This statement can be readily debated, but in my mind, network analysis is a field within GISciences that perhaps has the most tangible impact on our daily lives, and can be applied to the most diverse types of phenomena. The authors highlight routing as one of the most fundamental operations in network analysis, and I couldn’t imagine our society functioning without it. Routing is particularly relevant in urban areas where efficient movement from point A to point B across complex road systems is essential for the transportation of people and goods.
Shortest path routing may be the most basic implementation, but I am curious to understand how other factors can be incorporated into routing algorithms to enhance efficiency. The authors indicate that “many parameters can be set in order to define more complex versions of shortest path problems”. In urban areas, for example, how are factors such as traffic, road speed limits, and road condition integrated to provide better routing options?
In reading this article, I was reminded of a previous article that we read on spatial social networks (Radil et al., 2009). Both of these articles highlight the interesting role of space in network analysis. Networks are fundamentally spatial due to their graphical basis, but they can also be used to represent explicitly spatial geographic networks.