A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided CityCitation formats

  • External authors:
  • Duncan Whyatt
  • Bree Hocking
  • Brendan Sturgeon
  • Gemma Davies
  • John Dixon
  • Neil Jarman
  • Dominic Bryan

Standard

A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City. / Huck, Jonathan; Whyatt, Duncan; Hocking, Bree; Sturgeon, Brendan; Davies, Gemma; Dixon, John; Jarman, Neil; Bryan, Dominic .

: Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.. 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Huck, J, Whyatt, D, Hocking, B, Sturgeon, B, Davies, G, Dixon, J, Jarman, N & Bryan, D 2018, A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City. in : Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK..

APA

Huck, J., Whyatt, D., Hocking, B., Sturgeon, B., Davies, G., Dixon, J., ... Bryan, D. (2018). A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City. In : Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.

Vancouver

Huck J, Whyatt D, Hocking B, Sturgeon B, Davies G, Dixon J et al. A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City. In : Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.. 2018

Author

Huck, Jonathan ; Whyatt, Duncan ; Hocking, Bree ; Sturgeon, Brendan ; Davies, Gemma ; Dixon, John ; Jarman, Neil ; Bryan, Dominic . / A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City. : Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.. 2018.

Bibtex

@inproceedings{58f2536b3abd4db28d2fd924eb016ab9,
title = "A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City",
abstract = "This paper presents an alternative approach to the measurement of segregation that uses Bayesian statistics to combine information on residents’ perceptions (PGIS) and behaviour (GPS tracking) in order to generate probabilistic surfaces of ‘community belonging’ for each of the main communities in the study area. Because these surfaces are based upon both perception and behaviour, they are not limited to either residential or activity-space segregation and they also avoid several problems associated with traditional, census based analyses such as homogeneity within areal units and the modifiable areal unit problem. These surfaces are then assessed for segregation and scale sensitivity using a modified version of the lacunarity metric for spatial heterogeneity, in order to demonstrate how this approach has the potential to give new insights into the use and segregation of space, which is illustrated using a case study in North Belfast, Northern Ireland.",
author = "Jonathan Huck and Duncan Whyatt and Bree Hocking and Brendan Sturgeon and Gemma Davies and John Dixon and Neil Jarman and Dominic Bryan",
year = "2018",
month = "4",
language = "English",
booktitle = ": Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.",

}

RIS

TY - GEN

T1 - A Bayesian Approach to ‘Community Belonging’ and Segregation in a Divided City

AU - Huck, Jonathan

AU - Whyatt, Duncan

AU - Hocking, Bree

AU - Sturgeon, Brendan

AU - Davies, Gemma

AU - Dixon, John

AU - Jarman, Neil

AU - Bryan, Dominic

PY - 2018/4

Y1 - 2018/4

N2 - This paper presents an alternative approach to the measurement of segregation that uses Bayesian statistics to combine information on residents’ perceptions (PGIS) and behaviour (GPS tracking) in order to generate probabilistic surfaces of ‘community belonging’ for each of the main communities in the study area. Because these surfaces are based upon both perception and behaviour, they are not limited to either residential or activity-space segregation and they also avoid several problems associated with traditional, census based analyses such as homogeneity within areal units and the modifiable areal unit problem. These surfaces are then assessed for segregation and scale sensitivity using a modified version of the lacunarity metric for spatial heterogeneity, in order to demonstrate how this approach has the potential to give new insights into the use and segregation of space, which is illustrated using a case study in North Belfast, Northern Ireland.

AB - This paper presents an alternative approach to the measurement of segregation that uses Bayesian statistics to combine information on residents’ perceptions (PGIS) and behaviour (GPS tracking) in order to generate probabilistic surfaces of ‘community belonging’ for each of the main communities in the study area. Because these surfaces are based upon both perception and behaviour, they are not limited to either residential or activity-space segregation and they also avoid several problems associated with traditional, census based analyses such as homogeneity within areal units and the modifiable areal unit problem. These surfaces are then assessed for segregation and scale sensitivity using a modified version of the lacunarity metric for spatial heterogeneity, in order to demonstrate how this approach has the potential to give new insights into the use and segregation of space, which is illustrated using a case study in North Belfast, Northern Ireland.

M3 - Conference contribution

BT - : Proceedings of the GIS Research UK 28th Annual Conference, Leicester, UK.

ER -