Commuting flows & local labour markets: Spatial interaction modelling of travel-to-work

One of the most promising approaches to mitigating land-use and transportation problems is continued research on urban commuting. Commuting is essential to many individuals, allowing them to participate in the labour market and earn a living to meet their essential needs. As such, a better understanding of the determinants of commuting will ultimately lead to a better understanding of the complexities of employment, housing, and the many spatial processes underlying commuting. However, in order to understand the commuting process, it is important to examine the milieu within which commuting takes place: the local labour market (LLM). In this thesis, the interplay between commuting and LLMs is explored through the use of regionalisation techniques and spatial interaction models. It is shown that LLM characteristics play a significant role in intra-regional commuting patterns and that a failure to account for LLM conditions may seriously hinder the applicability of models of commuting. Specically, it is found that there are many dierent LLMs across Ireland, and that these LLMs characterise the commuting patterns of population sub-groups. By incorporating these LLMs into models of commuting, this thesis shows that in addition to distance and working population size, the spatial structure of origins and destinations and a number of non-spatial attributes such as unemployment, housing density, and education, all signi- cantly aect commuting ows. Furthermore, the distance decay component of these models appears to be capturing a combination of geographical distance and regional dierentiation due to LLM boundaries, leading to `functional' distance decay. This concept of functional distance decay is a key nding of this thesis, and indicates that in addition to the conguration of origins and destinations, distance decay is also dependent on the spatial structure of LLMs, or more generally, the totality of surrounding conditions within which spatial interaction takes place

Mapping the effects of the modifiable areal unit problem on local measures of spatial autocorrelation

Honors Thesis, University of Victoria, Victoria, British Columbia, Canad

Commuting flows & local labour markets: Spatial interaction modelling of travel-to-work

PhD Thesis, National University of Ireland, Maynooth, Co. Kildare, Irelan

Network-based functional regions

For administration efficiency most countries subdivide their national territory into administrative regions. These regions are used to delineate areas which are internally well connected and relatively cohesive, especially compared with the links between regions. Hence, many countries seek to delineate local labour markets (LLMs): geographical regions where the majority of the local population seeks employment and from which the majority of local employers recruit labour. LLM boundaries are often based on functional regions, which represent the aggregate commuting patterns of the local population. A number of regionalisation procedures for objectivity delineating functional regions have been suggested, though many of these procedures require the use of ad hoc parameters to control the size and number of regions. Recently, a range of network-based alternatives have been developed in the literature. One of the most successful such methods is based on the concept of modularity: the extent to which there are dense connections within functional regions, but only sparse connections between functional regions. In this paper we maximise the modularity of a network of commuting flows to produce a regionalisation that exhibits less interaction than expected between regions. We demonstrate the effectiveness of this type of regionalisation procedure on a simulated geographical network, as well as using commuting data for the Republic of Ireland. We suggest that this new method has specific advantages over existing regionalisation procedures, particularly in the context of disaggregate commuting patterns of socioeconomic subgroups.</p

Community detection in spatial networks: Inferring land use from a planar graph of land cover objects

This paper applies three algorithms for detecting communities within networks. It applies them to a network of land cover objects, identified in an OBIA, in order to identify areas of homogenous land use. Previous research on land cover to land use transformations has identified the need for rules and knowledge to merge land cover objects. This research shows that Walktrap, Spinglass and Fastgreedy algorithms are able to identify land use communities but with different spatial properties. Community detection algorithms, arising from graph theory and networks science, offer methods for merging sub-objects based on the properties of the network. The use of an explicitly geographical network also identifies some limitations to network partitioning methods such as Spinglass that introduce a degree of randomness in their search for community structure. The results show such algorithms may not be suitable for analysing geographic networks whose structure reflects topological relationships between objects. The discussion identifies a number of areas for further work, including the evaluation of different null statistical models for determining the modularity of geographic networks. The findings of this research also have implications for the many activities that are considering social networks, which increasingly have a geographical component