Abstract
Monitoring Networks topology and resolutions (spatial and dimensional/fractal) influence the ability of networks to detect spatial phenomena. In the present paper we consider several fundamental questions related to the clustering of monitoring networks and their ability (1) to detect spatial phenomena and (2) to reproduce spatial patterns using geostatistical simulations. Artificial monitoring networks with known level of clustering characterized by their fractal dimension are sampled on a same reference image with known spatial structure. Subsequently, these networks are used to interpolate using Sequential Gaussian Simulation. Resulting images are compared with several methods. Clustering of networks does not harm global detection of spatial structures (i.e., definition of correct variogram model), but influence heavily the uncertainty related to these maps, especially in tasks of detection of areas-at-risk.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Caeiro, S., Painho, M., Goovaerts, P., Costa, H., Sousa, S. (2003), Spatial sampling design for sediment quality assessment in estuaries. Environmental Modelling & Software, 18:853–859.
Christakos, G. (1992), Random Fields Models in Earth Sciences. San Diego, Academic Press.
De Gruijter J., Brus D., Bierkens M., Knotters M. (2006), Sampling for Natural Resource Monitoring. Berlin Heidelberg, Springer-Verlag.
Deutsch, C., Journel, A. (1997), GSLIB. Geostatistical Software Library and User‘s Guide. New York, Oxford University Press.
Falconer, K.J. (1990), Fractal Geometry. Mathematical Foundations and Applications. Chichester, John Wiley and Sons.
Kanevski M., Maignan M. (2004), Analysis and Modelling of Spatial Environmental Data. Lausanne, EPFL Press.
Lovejoy S., Schertzer D., Ladoy P. (1986). Fractal characterisation of inhomogeneous geophysical measuring networks. Nature, 319: 43–44.
Markus, A., Welch, W.J., Sacks, J. (1999), Design and analysis for modeling and predicting spatial contamination. Mathematical Geology, 31(1):1–22.
McGarigal, L., Marks, B.J. (1994), FRAGSTATS manual: spatial pattern analysis program for quantifying landscape structure. http://www.umass.edu/landeco/research/fragstats/ fragstats.html
O’Neill, R.V., Krummel, J.R., Gardner, R.H., Sugihara, G., Jackson, B., DeAngelis, D.L., Milne, B.T., Turner, M.G., Zygmunt, B., Christensen, S.W., Dale, V.H., Graham, R.L. (1988), Indices of landscape pattern. Landscape Ecology, 1:153–162.
Peitgen, H.O., Hartmut, J., Saupe, D. (1992), Chaos and Fractals: New Frontiers of Science. New York, Springer-Verlag.
Richmond A. (2002), Two-point declustering for weighting data pairs in experimental variogram calculations. Computers and Geosciences, 28: 231–241.
Tuia, D., Kanevski, M. (2006), Indoor Radon Data Monitoring Networks: Topology, Fractality and Validity Domains, Congress of the International Association of Mathematical Geology (IAMG), Liège, Belgium.
Turner, M.G., Gardner, R.H., O’Neill, R.V. (Eds) (2001), Landscape Ecology in Theory and Practice: Pattern and Process. Springer-Verlag, New York.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Tuia, D., Kaiser, C., Kanevski, M. (2008). Clustering in Environmental Monitoring Networks: Dimensional Resolutions and Pattern Detection. In: Soares, A., Pereira, M.J., Dimitrakopoulos, R. (eds) geoENV VI – Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6448-7_41
Download citation
DOI: https://doi.org/10.1007/978-1-4020-6448-7_41
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-6447-0
Online ISBN: 978-1-4020-6448-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)