Abstract
The environmental risk assessment involves the analysis of complex phenomena. Different kinds of information, such as environmental, socio-economic, political and institutional data, are usually collected. In this chapter, spatio-temporal geostatistical analysis is combined with the use of a Geographic Information System (GIS): the integration between geostatistical tools and GIS enables the identification and the visualization of alternative scenarios regarding a phenomenon under study and supports the environmental risk management.
A case study on environmental data measured at different monitoring stations in the southern part of Apulia Region (South of Italy), called Grande Salento, is discussed. Sample data concerning daily averages of PM10, Wind Speed and Atmospheric Temperature, are used for stochastic prediction, through space–time indicator kriging.
Kriging results are implemented in a GIS and a 3D representation of the spatio-temporal probability maps is proposed.
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Acknowledgements
The authors would like to thank Prof. D. Posa for his helpful suggestions and Prof. S. De Iaco for supporting the research activities involved in this paper by the Project “5 per mille per la ricerca” entitled “Modelli di Interpolazione Stocastica per il Monitoraggio Ambientale: Sviluppi Teorici e Applicativi”, University of Salento (2011–2012).
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Maggio, S., Cappello, C., Pellegrino, D. (2013). GIS and Geostatistics for Supporting Environmental Analyses in Space-Time. In: Montrone, S., Perchinunno, P. (eds) Statistical Methods for Spatial Planning and Monitoring. Contributions to Statistics. Springer, Milano. https://doi.org/10.1007/978-88-470-2751-0_4
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DOI: https://doi.org/10.1007/978-88-470-2751-0_4
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