5.2.1 Why “Field”?

In traditional land valuation, urban land value is usually represented as a set of discrete prices associated with individual parcels or transactions. Each parcel is treated as an isolated observation, and the primary objective is to estimate its market value at a particular moment in time.

However, urban value does not emerge independently at each parcel. Infrastructure networks, accessibility, economic activities, public investment, planning regulations, environmental quality, and social interactions create spatial influences that extend beyond parcel boundaries. Value generated at one location often affects surrounding areas, producing gradients, clusters, corridors, and diffusion patterns across the city.

These characteristics suggest that urban land value behaves more like a continuous spatial phenomenon than a collection of unrelated point values. A new transportation corridor, for example, does not increase value only at a single parcel; its influence propagates through adjacent neighborhoods and along connected urban networks. Similarly, economic agglomeration, public services, and environmental improvements generate effects that spread across space with varying intensity.

In physics and mathematics, such phenomena are commonly represented as fields. A field assigns a value to every location in space and allows the analysis of spatial continuity, gradients, interactions, and temporal evolution. By adopting this concept, the Urban Land Value Field (ULVF) models urban land value as a continuous function distributed across geographic space and evolving through time.

The field perspective offers several advantages:

• Continuity: Value can be analyzed at any location, not only where transactions occur.

• Spatial interaction: The influence of infrastructure and surrounding areas can be quantified.

• Dynamic evolution: Changes in value can be modeled through time.

• Multi-scale analysis: Value patterns can be examined from parcel level to corridor and metropolitan scales.

• Integration with GIS and AI: Continuous fields provide a natural foundation for spatial analytics, machine learning, and urban simulation.

Therefore, the term “Field” is not merely a descriptive metaphor. It represents a mathematical and spatial framework in which urban land value is understood as a continuously evolving urban phenomenon shaped by interconnected processes across the entire city.

The discussions presented in this section are primarily based on the following references: 

[18] Goodchild, M. F. (2007). Citizens as Sensors: The World of Volunteered Geography.

[19] Batty, M. (2013). The New Science of Cities.

[20] Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. Geographic Information Systems and Science.