Be sure to also check out our Presentations page!


Chen, H., Cheng, T. & Wise, S. (2017) Developing an Online Cooperative Police Patrol Routing Strategy. Computers, Environment and Urban Systems.

Kempinska, K., Davies, T., Shawe-Taylor, J. & Longley P. (2017) Probabilistic Map-Matching for Low-Frequent GPS Trajectory. GIS Ostrava 2017 (Ostrava, Czech)


Cheng, T. et al. (2016) CPC: Crime, Policing and Citizenship – Intelligent policing and big data. SpaceTimeLab, London.

Adepeju, M., Rosser, G. & Cheng, T. (2016) Novel Evaluation Metrics for Sparse Spatio-Temporal Point Process Hotspot Predictions – a Crime Case Study. International Journal of Geographical Information Science.

Rosser, G. & Cheng, T. (2016) Practical implementation and accuracy evaluation of a self-exciting point process for crime data. (Technical Report)

Rosser, G. & Cheng, T. (2016) Improving the Robustness and Accuracy of Crime Prediction with the Self-Exciting Point Process Through Isotropic Triggering. Applied Spatial Analysis and Policy.

Wang, J., Tsapakis, I. & Zhong, C. (2016) A Space–time Delay Neural Network Model for Travel Time Prediction. Engineering Applications of Artificial Intelligence.

Rosser, G., Davies, T., Bowers, K., Johnson, S. D. & Cheng, T. (2016). Predictive Crime Mapping: Arbitrary Grids or Street Networks? Journal of Quantitative Criminology

Shen, J. & Cheng, T. (2016) A framework for identifying activity groups from individual space-time profiles. International Journal of Geographical Information Science.

Wise, S. & Cheng, T. (2016) How Officers Create Guardianship: An Agent-based Model of Policing. Transactions in GIS. doi:10.1111/tgis.12173.

Chow, A. (2016) Heterogeneous urban traffic data and their integration through kernel-based interpolation. Journal of Facilities Management.

Kempinska, K., Davies, T. & Shawe-Taylor, J. (2016) Probabilistic Map-Matching Using Particle Filters. GISRUK 2016 Conference (Greenwich, UK)

Williams, D., Haworth, J., & Cheng, T. (2016) Predicting Public Confidence in the Police with Spatiotemporal Bayesian Hierarchical Modelling. GISRUK 2016 Conference (Greenwich, UK)

Kempinska, K. & Shawe-Taylor, J. (2016) Improved Particle Filters for Vehicle Localisation. NIPS 2016 Advances in Bayesian Inference Workshop (Barcelona, Spain)

Anbaroglu, B., Heydecker, B. & Cheng, T. (2016) How Travel Demand Affects Detection of Non-Recurrent Traffic Congestion on Urban Road Networks. ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

Sfyridis A. (2016) Data Driven Knowledge Extraction from a Large Dataset of Vessel Positions Using Data Mining Algorithms. Thesis. University College London.

Zhao, J. (2016) Predicting Users’ Home Address with Oyster Card Data and London Travel Demand Survey Data. Thesis. University College London.

Liu, Y. (2016) Space-Time Pattern Analysis of Oyster Card Data. Thesis. University College London.

Tian, J. (2016) How Twitter Impact Sexually Transmitted Infections in London? Thesis. University College London.

Petrova, D. (2016) Space-time modelling of sexually transmitted infections in London with focus on Chlamydia Trachomatis. Thesis. University College London.


Adepeju, M., Cheng, T., Shawe-Taylor, J., & Bowers, K. (2015) A new metric of crime hotspots for operational Policing. GISRUK 2015 Conference (Leeds, UK).

Chen, H., Cheng, T. & Wise, S. Designing daily patrol routes for policing based on ant colony algorithm. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-4/W2, 103–109.

Davies, T. & Bowers, K. (2015) Quantifying the deterrent effect of police patrol via GPS analysis. GISRUK 2015 Conference (Leeds, UK).

Davies, T. & Marchione, E. (2015). Event Networks and the Identification of Crime Pattern Motifs. PLoS ONE 10(11): e0143638. doi:10.1371/ journal.pone.0143638.

Gale, C.G., Singleton, A. D. and Longley, P. A. (2015) Profiling Burglary in London using Geodemographics. GISRUK 2015 Conference (Leeds, UK).

Kempinska, K., Shawe-Taylor, J., & Longley, P. (2015) Data-driven modelling of police route choice. GISRUK 2015 Conference (Leeds, UK).

Kempinska, K., Manley, E. & Shawe-Taylor, J. (2015) Routing regions: extracting spatial patterns from drivers’ preferences. Plurimondi. An International Forum for Research and Debate on Human Settlements.

Lai, J., Cheng, T., & Lansley, G. (2015) Spatio-Temporal Patterns of Passengers’ Interests at London Tube Stations. GISRUK 2015 Conference (Leeds, UK).

Rosser, G. & Cheng, T. (2015) A self-exciting point process model for predictive policing: implementation and evaluation. GISRUK 2015 Conference (Leeds, UK).

Shen, J. & Cheng, T. (2015) Group Behaviour Analysis of London Foot Patrol Police. GISRUK 2015 Conference (Leeds, UK).

Shen, J. & Cheng, T. (2015) Clustering Analysis of London Police Foot Patrol Behaviour from Raw Trajectories. In Proc of the 13th International Conference on GeoComputation, Richardson, USA, May, 2015.

Singleton, A.D. & Longley, P.A. (2015) The Internal Structure of Greater London: A Comparison of National and Regional Geodemographic Models. Geo: Geography and Environment.

Williams, D., Haworth, J., & Cheng, T. (2015) Exploratory spatiotemporal data analysis of public confidence in the police in London. GISRUK 2015 Conference (Leeds, UK).

Wise, S. & Cheng, T. (2015) A Model Officer: An Agent-based Model of Policing. GISRUK 2015 Conference (Leeds, UK).



Visualisation of street segments coloured according to their betweenness for (a) the entire street network of Birmingham, and (b) one smaller section. Taken from Davies & Johnson, 2014.

Adepeju, M. & Cheng, T. (2014) Prospective Space-Time Scan Statistics (STSS) for Crime Prediction. GISRUK 2014 Conference (Glasgow, UK).

Cheng, T., & Adepeju, M. (2014). Modifiable Temporal Unit Problem (MTUP) and its effect on space-time cluster detection. PloS one, 9(6), e100465.

Cheng, T., & Wicks, T. (2014). Event Detection using Twitter: A Spatio-Temporal Approach. PloS one, 9(6), e97807.


Davies, T. & Johnson, S.D. (2014). Examining the Relationship Between Road Structure and Burglary Risk Via Quantitative Network Analysis. Journal of Quantitative Criminology.

Gale, C.G., Singleton, A. D. and Longley, P. A. (2014). Does London need a separate geodemographic classification? GISRUK 2014 Conference (Glasgow, UK).

Gale, C.G., Singleton, A.D., Longley, P.A. (2014). Creating the 2011 Area Classification for Output Areas (2011 OAC). Journal of the Royal Statistical Society Series A.

Rosser, G. & Cheng, T. (2014) Point process models for prospective crime analysis. GISRUK 2014 Conference (Glasgow, UK).

Rosser, G. Crime prediction with the self-exciting point process (2015). Technical report.

Williams, D., Cheng, T. & Haworth, J. (2014) Examining the spatio-temporal structure of public confidence in the police. GISRUK 2014 Conference (Glasgow, UK).


Bowers, K., and Guerette, R. (2013). Evaluation of Situational Crime Prevention. In Bruinsma, G and Weisburd, D, (eds.) Encyclopedia of Criminology and Criminal Justice. Springer Verlag

Cheng, T., & Adepeju, M. (2013). Detecting emerging space-time crime patterns by prospective STSS. In Proc of the 12th International Conference on GeoComputation, Wuhan, China, May, 2013.

Cheng, T., Tanaksaranond, G., Brunsdon, C., Haworth, J. (2013). Exploratory visualisation of congestion evolutions on urban transport networks, Transportation Research Part C: Emerging Technologies, 36, 296-306.

Chow, A. H.F., Santacreu, A., Tsapakis, I., Tanasaranond, G. and Cheng, T. (2013). Empirical assessment of urban traffic congestion. J. Adv. Transp.

Johnson, S., and Bowers, K. (2013). Near repeats and crime forecasting. In Bruinsma, G and Weisburd, D, (eds.) Encyclopedia of Criminology and Criminal Justice. Springer Verlag.

Skarlatidou, A., Cheng, T., and Haklay, M. (2013). Guidelines for trust interface design for public engagement Web GIS , International Journal of Geographical Information Science, 27(8)

Tsapakis, T., Cheng, T., Bolbol, A. (2013). Impact of weather conditions on macroscopic urban travel times, Journal of Transport Geography, 28, 204-211.

Cheng et al, 2012

Studying autocorrelation between locations at various times of day. Excerpt from Cheng et al, 2012.


Bolbol, A., Cheng, T., Tsapakis, I., & Haworth, J. (2012). Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification. Computers, Environment and Urban Systems.

Cheng T., Haworth J. and Manley E. (2012). Advances in Geocomputation (1996-2011). Computers, Environment and Urban Systems, in press.

Cheng T., Haworth J. and Wang J. (2012). Spatio-temporal autocorrelation of road network data. Journal of Geographical Systems, 14, 389-413.

Eva W., (2012). Spatial Hotspot Analysis of Crime Incidents in Camden by Incident Type. Thesis. University College London.

Haworth, J., & Cheng, T. (2012). Non-parametric regression for space–time forecasting under missing data. Computers, Environment and Urban Systems.

Johnson, S., and Bowers, K. (2012). Crime Displacement and Diffusion of Benefits; A review of situational crime prevention measures. In Welsh, BC and Farrington, DP, (eds.) The Oxford Handbook of Crime Prevention. Oxford University Press.

Johnson, S., Bowers, K., and Pease, K. (2012). Towards the Modest Predictability of Daily Burglary Counts. Policing, 6(2), 167-176.

Monsuru A. (2012). Exploratory Space-Time Data Analysis (ESTDA) of Crime Patterns in Central London: Crime Emerging Patterns (Clusters) Detection. Thesis. University College London.

Visualisation of study area with dataset utilised in Bolbol et al, 2012.

Visualisation of study area with dataset utilised in Bolbol et al, 2012.

Older Publications

Andrew S. (2011). A comparison of hotspot mapping for crime incident prediction. Thesis. University College London.

Cheng T., Wang J., and Li X. (2011). A hybrid framework for space-time modelling of environmental data. Geographical Analysis, 43(2), 188-210.

Adnan M., Longley P.A., Singleton A.D. and Brunsdon C. (2010). Towards real-time geodemographics: clustering algorithm performance for large multidimensional spatial databases. Transactions in GIS, 14: 283-97.

Cheng T. and Anbaroglu B. (2010). Spatio-temporal clustering of road network data. International Conf. on Artificial Intelligence and Computer Intelligence, LNCS, 6319: 116-123.

Wang J., Cheng T. and Haworth J. (2010). Space-time kernels. In: Shi, W and Goodchild, M and Lees, B, (eds.) Advances in geospatial information science. CRC Press: Leiden, NL.

Cheng T. and Wang J. (2009). Accommodating spatial associations in DRNN for space–time analysis. Computer, Environmental, and Urban System. 33: 409-418.

Cheng T. and Wang, J. (2008). Integrated spatio-temporal data mining for forest fire prediction.Transactions in GIS, 12: 591-611.

Ashby D.I. and Longley P.A. (2005). Geocomputation, geodemographics and resource allocation for local policing. Transactions in GIS 9: 53-72.

Bowers K.J. and Johnson S.D. (2005). Domestic burglary repeats and space–time clusters: the dimensions of risk. European Journal of Criminology 2:67-92.

Longley PA, (2005). A renaissance of geodemographics for public service delivery. Progress in Human Geography, 29: 57-63

Shawe-Taylor J. and Cristianini N. (2004). Kernel Methods for Pattern Analysis.

Shawe-Taylor J. and Cristianini N. (2000). An Introduction to Support Vector Machines.