Abstract
A 911 call may be a result of an emergency medical need, fire attack, natural disaster, crime or an individual or group of persons needing some form of emergency assistance. Policy makers are normally faced with difficult decisions of providing resources to handle these emergencies, but due to lack of data and their inability to foresee the occurrences of these problems, they are caught by surprise. In this paper, we develop a model that will help policy makers anticipate the occurrences of emergencies. Spatial analysis methods such as hotspot analysis are used that can help policy makers distribute resources fairly by needs.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cassetti, E.: The expansion method. Journal of Information Science, 432–449 (1972)
Chris, B., Martin, C., Stewart, F.: Geographically weigthed regresion - modelling spatial non stationarity. The Statistician, 431–443 (1998)
ESRI: ArcGIS Desktop Help 9.3 (2009), http://webhelp.esri.com/arcgisdesktop/9.3
ESRI Developer network: Hot Spot Analysis (Getis-Ord Gi*) (spatial statistics), http://edndoc.esri.com/arcobjects/9.2
Fotheringham, A.S., Brunsdon, C., Charlton, M.: Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)
GIS Blog: GIS Data, http://www.gisiana.com
Gorr, W.L., Olligschlaeger, A.M.: Weighted spatial adaptive filtering: Monte Carlo studies and application to illicit drug market modeling. Geography Analysis, 67–87 (1994)
Grubesic, T.H., Murray, A.T.: Detecting hot spots using cluster analysis and gis. In: Proceedings from the Fifth Annual International Crime Mapping Research Conference (2001)
Hodgkiss, W., Baru, C., Fountain, T.R., Reich, D., Warner, K., Glasscock, M.: Spatiotemporal analysis of 9-1-1 call stream data. In: Proceedings of the 2005 National Conference on Digital Government Research, pp. 293–294, Digital Government Society of North America (2005)
Jasso, H., Fountai, T., Baru, C., Hodgkiss, W., Reich, D., Warner, K.: Prediction of 9-1-1 call volumes for emergency event detection. In: Proceedings of the 8th Annual International Conference on Digital Government Research: Bridging Disciplines & Domains, pp. 148–154. ACM, New York (2007)
Kuhn, P., Hoey, T.P.: Improving 911 police operation, pp. 125–130. National Productivity, Washington, D.C (1987)
Tandberg, D., Easom, L.J., Qualls, C.: Time series forecasts of poison center call volume. Clinical Toxicology 33(1), 11–18 (1995)
Zeng, D., Chang, W., Chen, H.: A comparative study of spatio-temporal hotspot analysis techniques in security informatics. In: Proceedings of 7th International IEEE Conference on Intelligent Transportation Systems, pp. 106–111. IEEE, Los Alamitos (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Cramer, D., Brown, A.A., Hu, G. (2012). Predicting 911 Calls Using Spatial Analysis. In: Lee, R. (eds) Software Engineering Research,Management and Applications 2011. Studies in Computational Intelligence, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23202-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-23202-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23201-5
Online ISBN: 978-3-642-23202-2
eBook Packages: EngineeringEngineering (R0)