@inproceedings{70b7de03370d40cbb611b5103991618a,
title = "Indoor radon data monitoring networks: Topology, fractality and validity domains",
abstract = "Analysis and quantification of monitoring networks structure (non-homogeneity or clustering) is an essential task for the characterization of networks' ability to detect phenomena under study. Clustering of monitoring networks has a considerable influence on the quality of univariate data analysis (distributions modelling) and on the consequent spatial predictions and simulations. In the present paper fractal measures/indexes are used in order to quantify monitoring networks. Comparison of the real Swiss Indoor Radon Monitoring Network (SIRMN) with simulated random networks on different validity domains shows the high degree of clustering of the network and the relevancy of the use of validity domains to predict the phenomenon. Multifractal analysis of real monitoring network has been used to reveal the distribution of spatial patterns of radon elevated concentrations.",
keywords = "Fractality, Indoor radon, Monitoring network, Spatial clustering, Validity domains",
author = "D. Tuia and M. Kanevski",
year = "2006",
language = "English",
isbn = "9782960064407",
series = "IAMG 2006 - 11th International Congress for Mathematical Geology: Quantitative Geology from Multiple Sources",
publisher = "International Association for Mathematical Geology, IAMG 2006",
booktitle = "IAMG 2006 - 11th International Congress for Mathematical Geology",
note = "11th International Congress for Mathematical Geology: Quantitative Geology from Multiple Sources, IAMG 2006 ; Conference date: 03-09-2006 Through 08-09-2006",
}