Editorial: Spatial Interaction Modelling

Guest Editorial Spatial agent-based modelling

The convergence of object-oriented approaches to data modelling within geographic information science together with increasingly fine-scale data collection approaches and discrete-event simulations has created new opportunities to build dynamic representations of geographical systems (Gimblett 2002, Brown et al. 2005). In particular, agent-based modelling has become an important representationa...

Principles of Neural Spatial Interaction Modelling

The focus of this paper is on the neural network approach to modelling origin-destination flows across geographic space. The novelty about neural spatial interaction models lies in their ability to model non-linear processes between spatial flows and their determinants, with few – if any – a priori assumptions of the data generating process. The paper draws attention to models based on the theo...

From Conventional to Neural Spatial Interaction Modelling

Spatial Interaction Modelling on theConnection Machine 200

Spatial interaction models are used to simulate interactions between residents in a given area and some facility. Principal factors innuencing the degree of interaction are the distance from a household to the facility, the size and type of population within the area, the attractiveness of the facility and the competition from other facilities in the area. The spatial interaction model discusse...

Spatial modelling of railway noise propagation

In recent decades, population growth and progress of technology have shaped large and compact urban settlements. Existence of huge transportation systems and developed urban infrastructures are among the most important properties of modern cities. In spite of prompt transit and facilitated daily activities, development of transportation systems causes many problems, including traffic, air and n...