Geographically weighted spatial interaction (GWSI)
MetadataShow full item record
One of the key concerns in spatial analysis and modelling is to study and analyse similarities or dissimilarities between places over geographical space. However, ”global“ spatial models may fail to identify spatial variations of relationships (spatial heterogeneity) by assuming spatial stationarity of relationships. In many real-life situations spatial variation in relationships possibly exists and the assumption of global stationarity might be highly unrealistic leading to ignorance of a large amount of spatial information. In contrast, local spatial models emphasise differences or dissimilarity over space and focus on identifying spatial variations in relationships. These models allow the parameters of models to vary locally and can provide more useful information on the processes generating the data in different parts of the study area. In this study, a framework for localising spatial interaction models, based on geographically weighted (GW) techniques, has been developed. This framework can help in detecting, visualising and analysing spatial heterogeneity in spatial interaction systems. In order to apply the GW concept to spatial interaction models, we investigate several approaches differing mainly in the way calibration points (flows) are defined and spatial separation (distance) between flows is calculated. As a result, a series of localised geographically weighted spatial interaction (GWSI) models are developed. Using custom-built algorithms and computer code, we apply the GWSI models to a journey-to-work dataset in Switzerland for validation and comparison with the related global models. The results of the model calibrations are visualised using a series of conventional and flow maps along with some matrix visualisations. The comparison of the results indicates that in most cases local GWSI models exhibit an improvement over the global models both in providing more useful local information and also in model performance and goodness-of-fit.
Thesis, PhD Doctor of Philosophy
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Showing items related by title, author, creator and subject.
Spatial patterns and species coexistence : using spatial statistics to identify underlying ecological processes in plant communities Brown, Calum (University of St Andrews, 2012-11) - ThesisThe use of spatial statistics to investigate ecological processes in plant communities is becoming increasingly widespread. In diverse communities such as tropical rainforests, analysis of spatial structure may help to ...
A spatial fuzzy influence diagram for modelling spatial objects dependencies : a case study on tree-related electricity outages Zhang, Zhe; Demšar, Urška; Wang, Shaowen; Virrantaus, Kirsi (2018) - Journal articleSpatial objects can be interconnected and mutually dependent in complex ways. In Geographical Information Science, spatial objects’ topological relationships are not discussed together with their attributes’ dependencies, ...
The spatialities of ageing : evidencing increasing spatial polarisation between older and younger adults in England and Wales Sabater, Albert; Graham, Elspeth; Finney, Nissa (2017-03-08) - Journal articleBackground : With the proportion of older adults in Europe expected to grow significantly over the next few decades, a number of pertinent questions are raised about the socio-spatial processes that underlie residential ...