Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: The Case Study of Potenza Hilltop Town (Southern Italy)

Authors:
Maria Danese;Maurizio Lazzari;Beniamino Murgante
Affiliations:
CNR-IBAM, Tito Scalo (PZ), Italy 85050-I and L.I.S.U.T. - D.A.P.I.T., University of Basilicata, Potenza, Italy 85100;CNR-IBAM, Tito Scalo (PZ), Italy 85050-I;L.I.S.U.T. - D.A.P.I.T., University of Basilicata, Potenza, Italy 85100
Venue:
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
Year:
2008

Citing 5
Cited 12

An improved data-based algorithm for choosing the window width when estimating the density at a point

Computational Statistics & Data Analysis
A comparative study of several smoothing methods in density estimation

Computational Statistics & Data Analysis
Estimating probability surfaces for geographical point data: an adaptive kernel algorithm

Computers & Geosciences
A cross-validation bandwidth choice for kernel density estimates with selection biased data

Journal of Multivariate Analysis
Network density estimation: analysis of point patterns over a network

ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III

Integrated Geological, Geomorphological and Geostatistical Analysis to Study Macroseismic Effects of 1980 Irpinian Earthquake in Urban Areas (Southern Italy)

ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Geospatial Crime Scene Investigation --- From Hotspot Analysis to Interactive 3D Visualization

ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Geovisualization Approaches for Spatio-temporal Crime Scene Analysis --- Towards 4D Crime Mapping

IWCF '09 Proceedings of the 3rd International Workshop on Computational Forensics
Mapping the anthropic backfill of the historical center of Rome (Italy) by using intrinsic random functions of order k (IRF-k)

ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
Spatio-temporal analysis using urban-rural gradient modelling and landscape metrics

ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
Individual movements and geographical data mining. clustering algorithms for highlighting hotspots in personal navigation routes

ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
Geostatistics in historical macroseismic data analysis

Transactions on Computational Science VI
Towards 3d tactical intelligence assessments for crime scene analysis

ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
Am i safe in my home? fear of crime analyzed with spatial statistics methods in a central european city

ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
Analyzing the central business district: the case of sassari in the sardinia island

ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
Using spatial autocorrelation techniques and multi-temporal satellite data for analyzing urban sprawl

ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Spatial Data Mining for Highlighting Hotspots in Personal Navigation Routes

International Journal of Data Warehousing and Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper focuses on an overview of kernel density estimation especially for what concerns the choice of bandwidth and intensity parameters according to local conditions. A case study inherent seismic risk analysis of the old town centre of Potenza hilltop town has been discussed, with particular attention to the evaluation of the possible local amplifying factors. This first integrated application of kernel density maps to analyse seismic damage scenarios with a geostatistical approach allowed to evaluate the local geological, geomorphological and 1857 earthquake macroseismic data, offering a new point of view of civil protection planning. The aim of geostatistical approach is to know seismic risk variability at local level, modelling and visualizing it.