Journal Articles

2019

• Gulma UL; Evans A; Heppenstall A; Malleson N Diversity and Burglary: Does Community Differences Matter?. Transactions in GIS, In press.
• Arnold K; Harrison W; Heppenstall A; Gilthorpe M DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference. International Journal of Epidemiology, In press.

2018

• Burns L; See L; Heppenstall A; Birkin M (2018) Developing an Individual-level Geodemographic Classification, Applied Spatial Analysis and Policy, 11, pp.417-437. doi: 10.1007/s12061-017-9233-7
• Mustafa A; Heppenstall A; Omrani H; Saadi I; Cools M; Teller J (2018) Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm, Computers, Environment and Urban Systems, 67, pp.147-156. doi: 10.1016/j.compenvurbsys.2017.09.009
• Sturley C; Newing A; Heppenstall A (2018) Evaluating the potential of agent-based modelling to capture consumer grocery retail store choice behaviours, International Review of Retail, Distribution and Consumer Research, 28, pp.27-46. doi: 10.1080/09593969.2017.1397046
• Arnold KF; Ellison GTH; Gadd SC; Textor J; Tennant PWG; Heppenstall A; Gilthorpe MS (2018) Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges, Statistical Methods in Medical Research, . doi: 10.1177/0962280218756158
• Xiang L; Stillwell J; Burns L; Heppenstall A; Norman P (2018) A geodemographic classification of sub-districts to identify education inequality in Central Beijing, Computers, Environment and Urban Systems, 70, pp.59-70. doi: 10.1016/j.compenvurbsys.2018.02.002
• Owen A; Heppenstall A (2018) Making the case for simulation: Unlocking carbon reduction through simulation of individual ‘middle actor’ behaviour, Environment and Planning B: Urban Analytics and City Science, . doi: 10.1177/2399808318784597
• Jumadi; Heppenstall AJ; Malleson NS; Carver SJ; Quincey DJ; Manville VR (2018) Modelling individual evacuation decisions during natural disasters: A case study of volcanic crisis in Merapi, Indonesia, Geosciences (Switzerland), 8, . doi: 10.3390/geosciences8060196

2017

• Alotaibi, N., Evans, A., Heppenstall, A. and Malleson, N., (2017) How Well Does Western Environmental Theory Explain Crime in the Arabian Context? The Case Studyof Riyadh, Saudi Arabia. International Criminal Justice Review 1 – 28. DOI: 10.1177/1057567717709497
• Harris, R., O’Sullivan, D.,Comber, L., Longley, P., Brunsdon, C., Malleson, N., Heppenstall, A., Singleton, A. Arribas-Bel, D. and Evans A.J., (2017). More bark than bytes? Reflections on 21+ years of geocomputation. Environment and Planning B: Urban Analytics and City Science, 44(4), pp.598-617.

2016

• Whittle, M, Lomax, N., Heppenstall, A. and Brerton, S. (2016) Equitable or Elitist? The Social Impact of the 2014 Tour de France Grand Depart.  Area.  In press.
• Heppenstall A, Malleson, N. and Crooks, A. (2016) “Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities? Systems 2016, 4(1), 9; doi: 10.3390/systems4010009
• Olner D; Evans A; Heppenstall A (2015) An agent model of urban economics: Digging into emergence, Computers, Environment and Urban Systems, . doi: 10.1016/j.compenvurbsys.2014.12.003
• Ma J; Mitchell G; Heppenstall A (2015) Exploring transport carbon futures using population microsimulation and travel diaries: Beijing to 2030, TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 37, pp.108-122. doi: 10.1016/j.trd.2015.04.020
• Malleson N; See L; Evans A; Heppenstall A (2014) Optimising an Agent-Based Model to Explore the Behaviour of Simulated Burglars, Intelligent Systems Reference Library, 52, pp.179-204. doi: 10.1007/978-3-642-39149-1_12
• Clark SD; Birkin M; Heppenstall A (2014) Sub regional estimates of morbidities in the English elderly population, Health and Place, 27, pp.176-185. doi: 10.1016/j.healthplace.2014.02.010
• Ma J; Heppenstall A; Harland K; Mitchell G (2014) Synthesising carbon emission for mega-cities: A static spatial microsimulation of transport CO2 from urban travel in Beijing, Computers, Environment and Urban Systems, 45, pp.78-88. doi: 10.1016/j.compenvurbsys.2014.02.006
• Heppenstall A (2014) Complexity and planning: systems, assemblages and simulations, ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 41, pp.375-376.
• Ma J; Mitchell G; Heppenstall A (2014) Daily travel behaviour in Beijing, China.An analysis of workers’ trip chains, and the role of socio-demographics and urban form, Habitat International, 43, pp.263-273. doi: 10.1016/j.habitatint.2014.04.008
• Malleson N; Heppenstall A; See L; Evans A (2013) Using an agent-based crime simulation to predict the effects of urban regeneration on individual household burglary risk, Environment and Planning B: Planning and Design, 40, pp.405-426. doi: 10.1068/b38057
• Heppenstall A (2013) Advanced Geosimulation Models, APPLIED SPATIAL ANALYSIS AND POLICY, 6, pp.251-253. doi: 10.1007/s12061-012-9081-4
• Heppenstall AJ; Harland K; Olner D; Ross AN (2013) Simulating Spatial Dynamics and Processes in a Retail Gasoline Market: An Agent-Based Modeling Approach, Transactions in GIS, . doi: 10.1111/tgis.12027
• Harland K; Heppenstall A; Smith D; Birkin M (2012) Creating realistic synthetic populations at varying spatial scales: A comparative critique of population synthesis techniques, JASSS, 15, .
• Malleson N; See L; Evans A; Heppenstall A (2012) Implementing comprehensive offender behaviour in a realistic agent-based model of burglary, Simulation, 88, pp.50-71. doi: 10.1177/0037549710384124
• Birkin MH; Heppenstall AJ (2011) Extending Spatial Interaction Models with Agents for Understanding Relationships in a Dynamic Retail Market., Urban Studies Research, vol. 2011, Article ID 403969, .
• Malleson N; Heppenstall A; See L (2010) Crime reduction through simulation: An agent-based model of burglary, Computers, Environment and Urban Systems, 34, pp.236-250. doi: 10.1016/j.compenvurbsys.2009.10.005
• Al-Ahmadi K; Heppenstall A; Hogg J; See L (2009) A fuzzy cellular automata urban growth model (FCAUGM) for the city of Riyadh, Saudi Arabia. part 2: Scenario testing, Applied Spatial Analysis and Policy, 2, pp.85-105. doi: 10.1007/s12061-008-9019-z
• Al-Ahmadi K; Heppenstall A; Hogg J; See L (2009) A Fuzzy Cellular Automata Urban Growth Model (FCAUGM) for the City of Riyadh, Saudi Arabia. Part 1: Model Structure and Validation, Applied Spatial Analysis and Policy, 2, pp.65-83. doi: 10.1007/s12061-008-9020-6
• Calvo B; Napolitano G; Savi F; See L; Irvine B; Heppenstall A (2009) A conceptual and neural network model for real-time flood forecasting of the Tiber river in Rome, Proceedings of the IASTED International Conference on Modelling, Simulation, and Identification, MSI 2009, .
• Al-Ahmadi K; See L; Heppenstall A; Hogg J (2009) Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia, Ecological Complexity, 6, pp.80-101. doi: 10.1016/j.ecocom.2008.09.004
• Abrahart RJ; Heppenstall AJ; See LM (2007) Timing error correction procedure applied to neural network rainfall-runoff modelling, Hydrological Sciences Journal, 52, pp.414-431. doi: 10.1623/hysj.52.3.414
• Heppenstall AJ; Evans AJ; Birkin MH (2007) Genetic algorithm optimisation of an agent-based model for simulating a retail market, Environment and Planning B: Planning and Design, 34, pp.1051-1070. doi: 10.1068/b32068
• Abrahart RJ; See LM; Heppenstall AJ (2007) Neuroevolution applied to river level forecasting under winter flood and drought conditions, Journal of Intelligent Systems, 16, pp.373-386.
• Heppenstall AJ; See LM; Abrahart RJ (2007) Neuroevolution methodologies applied to sediment forecasting, IAHS-AISH Publication, pp.38-44.
• Dawson CW; See LM; Abrahart RJ; Heppenstall AJ (2006) Symbiotic adaptive neuro-evolution applied to rainfall-runoff modelling in northern England, Neural Networks, 19, pp.236-247. doi: 10.1016/j.neunet.2006.01.009
• Heppenstall AJ; Birkin MH; Evans AJ (2005) A hybrid multi-agent/spatial interaction model system for petrol price setting, Transactions in GIS, 9, pp.35-51.
• Heppenstall AJ; McFarland OE; Evans AJ (2005) Application of multi-agent systems and social network theory to petrol pricing on UK motorways, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3690 LNAI, pp.551-554. doi: 10.1007/11559221_58