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Documents authored by Comber, Alexis

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.17
Smarter Than Your Average Model - Bayesian Model Averaging as a Spatial Analysis Tool (Short Paper)

Authors: Chris Brunsdon, Paul Harris, and Alexis Comber

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Bayesian modelling averaging (BMA) allows the results of analysing competing data models to be combined, and the relative plausibility of the models to be assessed. Here, the potential to apply this approach to spatial statistical models is considered, using an example of spatially varying coefficient modelling applied to data from the 2016 UK referendum on leaving the EU.
Cite as

Chris Brunsdon, Paul Harris, and Alexis Comber. Smarter Than Your Average Model - Bayesian Model Averaging as a Spatial Analysis Tool (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 17:1-17:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{brunsdon_et_al:LIPIcs.GIScience.2023.17,
  author =	{Brunsdon, Chris and Harris, Paul and Comber, Alexis},
  title =	{{Smarter Than Your Average Model - Bayesian Model Averaging as a Spatial Analysis Tool}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{17:1--17:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.17},
  URN =		{urn:nbn:de:0030-drops-189123},
  doi =		{10.4230/LIPIcs.GIScience.2023.17},
  annote =	{Keywords: Bayesian, Varying coefficient regression, Spatial statistics}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.22
Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM) (Short Paper)

Authors: Alexis Comber, Paul Harris, and Chris Brunsdon

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
The paper develops a novel approach to spatially and temporally varying coefficient (STVC) modelling, using Generalised Additive Models (GAMs) with Gaussian Process (GP) splines parameterised with location and time variables - a Geographic and Temporal Gaussian Process GAM (GTGP-GAM). This was applied to a Mongolian livestock case study and different forms of GTGP splines were evaluated in which space and time were combined or treated separately. A single 3-D spline with rescaled temporal and spatial attributes resulted in the best model under an assumption that for spatial and temporal processes interact a case studies with a sufficiently large spatial extent is needed. A fully tuned model was then created and the spline smoothing parameters were shown to indicate the degree of variation in covariate spatio-temporal interactions with the target variable.
Cite as

Alexis Comber, Paul Harris, and Chris Brunsdon. Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM) (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 22:1-22:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{comber_et_al:LIPIcs.GIScience.2023.22,
  author =	{Comber, Alexis and Harris, Paul and Brunsdon, Chris},
  title =	{{Multiscale Spatially and Temporally Varying Coefficient Modelling Using a Geographic and Temporal Gaussian Process GAM (GTGP-GAM)}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{22:1--22:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.22},
  URN =		{urn:nbn:de:0030-drops-189173},
  doi =		{10.4230/LIPIcs.GIScience.2023.22},
  annote =	{Keywords: Spatial Analysis, Spatiotemproal Analysis}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.46
Status Poles and Status Zoning to Model Residential Land Prices: Status-Quality Trade off Theory (Short Paper)

Authors: Thuy Phuong Le, Alexis Comber, Binh Quoc Tran, Phe Huu Hoang, Huy Quang Man, Linh Xuan Nguyen, Tuan Le Pham, and Tu Ngoc Bui

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
This study describes an approach for augmenting urban residential preference and hedonic house price models by incorporating Status-Quality Trade Off theory (SQTO). SQTO seeks explain the dynamic of urban structure using a multipolar, in which the location and strength of poles is driven by notions of residential status and dwelling quality. This paper presents in outline an approach for identifying status poles and for quantifying their effect on land and residential property prices. The results show how the incorporation of SQTO results in an enhanced understanding of variations in land / property process with increased spatial nuance. A number of future research areas are identified related to the status pole weights and the development of status pole index.
Cite as

Thuy Phuong Le, Alexis Comber, Binh Quoc Tran, Phe Huu Hoang, Huy Quang Man, Linh Xuan Nguyen, Tuan Le Pham, and Tu Ngoc Bui. Status Poles and Status Zoning to Model Residential Land Prices: Status-Quality Trade off Theory (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 46:1-46:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{le_et_al:LIPIcs.GIScience.2023.46,
  author =	{Le, Thuy Phuong and Comber, Alexis and Tran, Binh Quoc and Hoang, Phe Huu and Man, Huy Quang and Nguyen, Linh Xuan and Le Pham, Tuan and Bui, Tu Ngoc},
  title =	{{Status Poles and Status Zoning to Model Residential Land Prices: Status-Quality Trade off Theory}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{46:1--46:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.46},
  URN =		{urn:nbn:de:0030-drops-189415},
  doi =		{10.4230/LIPIcs.GIScience.2023.46},
  annote =	{Keywords: spatial theory, house prices}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.78
Navigation in Complex Space: An Bayesian Nash Equilibrium-Informed Agent-Based Model (Short Paper)

Authors: Yiyu Wang, Jiaqi Ge, and Alexis Comber

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
This study proposed an improved pedestrian evacuation ABM employing Bayesian Nash Equilibrium (BNE) to simulate more realistic and representative individual evacuating behaviours in complex scenarios. A set of vertical blockades with adjustable gate widths was introduced to establish a simulation space with narrow corridor and bottlenecks and to evaluate the influences of BNE on individual navigation in complex space. To better match with the evacuating behaviours in real-world scenarios, the decision-making criterion of BNE evacuees was improved to a multi-strategy combination, with 80% of evacuees taking the optimal strategy, 15% taking sub-optimal strategy, and 5% taking the third-best one. The preliminary results demonstrate a positive impact of BNE on individual navigation in complex space, showing a distinct decrease of evacuation time with increasing proportion of BNE evacuees. The non-monotonicity of the variations in evacuation time also indicates the dynamic adaptability of BNE in addressing immediate challenges (i.e. blockades and congestions), which identifies alternative and potential faster paths during evacuations. A detailed description of the proposed ABM and an analysis of relevant experimental results are provided in this paper. Several limitations are also identified.
Cite as

Yiyu Wang, Jiaqi Ge, and Alexis Comber. Navigation in Complex Space: An Bayesian Nash Equilibrium-Informed Agent-Based Model (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 78:1-78:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wang_et_al:LIPIcs.GIScience.2023.78,
  author =	{Wang, Yiyu and Ge, Jiaqi and Comber, Alexis},
  title =	{{Navigation in Complex Space: An Bayesian Nash Equilibrium-Informed Agent-Based Model}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{78:1--78:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.78},
  URN =		{urn:nbn:de:0030-drops-189739},
  doi =		{10.4230/LIPIcs.GIScience.2023.78},
  annote =	{Keywords: Agent-based Modelling, Pedestrian Evacuation, Bayesian Nash Equilibrium, Individual Navigation, Complex Environment}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2022.13
Geographically Varying Coefficient Regression: GWR-Exit and GAM-On? (Short Paper)

Authors: Alexis Comber, Paul Harris, Daisuke Murakami, Narumasa Tsutsumida, and Chris Brunsdon

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
This paper describes initial work exploring two spatially varying coefficient models: multi-scale GWR and GAM Gaussian Process spline parameterised by observation location. Both approaches accommodate process spatial heterogeneity and both generate outputs that can be mapped indicating the nature of the process heterogeneity. However the nature of the process heterogeneity they each describe are very different. This suggests that the underlying semantics of such models need to be considered in order to refine the specificity of the questions that are asked of data: simply seeking to understand process spatial heterogeneity may be too semantically coarse.
Cite as

Alexis Comber, Paul Harris, Daisuke Murakami, Narumasa Tsutsumida, and Chris Brunsdon. Geographically Varying Coefficient Regression: GWR-Exit and GAM-On? (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 13:1-13:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{comber_et_al:LIPIcs.COSIT.2022.13,
  author =	{Comber, Alexis and Harris, Paul and Murakami, Daisuke and Tsutsumida, Narumasa and Brunsdon, Chris},
  title =	{{Geographically Varying Coefficient Regression: GWR-Exit and GAM-On?}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{13:1--13:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.13},
  URN =		{urn:nbn:de:0030-drops-168986},
  doi =		{10.4230/LIPIcs.COSIT.2022.13},
  annote =	{Keywords: Geographically weighted regression, Spatial Analysis, Process Spatial Heterogeneity, Model Semantics}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2022.21
A Comparison of Geographically Weighted Principal Components Analysis Methodologies (Short Paper)

Authors: Narumasa Tsutsumida, Daisuke Murakami, Takahiro Yoshida, Tomoki Nakaya, Binbin Lu, Paul Harris, and Alexis Comber

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
Principal components analysis (PCA) is a useful analytical tool to represent key characteristics of multivariate data, but does not account for spatial effects when applied in geographical situations. A geographically weighted PCA (GWPCA) caters to this issue, specifically in terms of capturing spatial heterogeneity. However, in certain situations, a GWPCA provides outputs that vary discontinuously spatially, which are difficult to interpret and are not associated with the output from a conventional (global) PCA any more. This study underlines a GW non-negative PCA, a geographically weighted version of non-negative PCA, to overcome this issue by constraining loading values non-negatively. Case study results with a complex multivariate spatial dataset demonstrate such benefits, where GW non-negative PCA allows improved interpretations than that found with conventional GWPCA.
Cite as

Narumasa Tsutsumida, Daisuke Murakami, Takahiro Yoshida, Tomoki Nakaya, Binbin Lu, Paul Harris, and Alexis Comber. A Comparison of Geographically Weighted Principal Components Analysis Methodologies (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 21:1-21:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{tsutsumida_et_al:LIPIcs.COSIT.2022.21,
  author =	{Tsutsumida, Narumasa and Murakami, Daisuke and Yoshida, Takahiro and Nakaya, Tomoki and Lu, Binbin and Harris, Paul and Comber, Alexis},
  title =	{{A Comparison of Geographically Weighted Principal Components Analysis Methodologies}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{21:1--21:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.21},
  URN =		{urn:nbn:de:0030-drops-169062},
  doi =		{10.4230/LIPIcs.COSIT.2022.21},
  annote =	{Keywords: Spatial heterogeneity, Geographically weighted, Sparsity, PCA}
}
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