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Geographical Disparities in Mortality Rates: Spatial Data Mining and Bayesian Hierarchical Modeling Read chapter Read first chapter

2013 | OriginalPaper | Chapter

4. GIS and Geostatistics for Supporting Environmental Analyses in Space-Time

Authors : Sabrina Maggio, Claudia Cappello, Daniela Pellegrino

Published in: Statistical Methods for Spatial Planning and Monitoring

Publisher: Springer Milan

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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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previous chapter Geostatistics and the Role of Variogram in Time Series Analysis: A Critical Review
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Metadata
Title
GIS and Geostatistics for Supporting Environmental Analyses in Space-Time
Authors
Sabrina Maggio
Claudia Cappello
Daniela Pellegrino
Copyright Year
2013
Publisher
Springer Milan
Book
Statistical Methods for Spatial Planning and Monitoring

Print ISBN: 978-88-470-2750-3

Electronic ISBN: 978-88-470-2751-0

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-88-470-2751-0_4

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