NDLI: An application of Spartan spatial random fields in environmental mapping: focus on automatic mapping capabilities

Content Provider	Springer Nature Link
Author	Elogne, Samuel N. Hristopulos, Dionissios T. Varouchakis, Emmauil
Copyright Year	2007
Abstract	This paper investigates the potential of Spartan spatial random fields (SSRFs) in real-time mapping applications. The data set that we study focuses on the distribution of daily gamma dose rates over part of Germany. Our goal is to determine a Spartan spatial model from the data, and then use it to generate “predictive” maps of the radioactivity. In the SSRF framework, the spatial dependence is determined from sample functions that focus on short-range correlations. A recently formulated SSRF predictor is used to derive isolevel contour maps of the dose rates. The SSRF predictor is explicit. Moreover, the adjustments that it requires by the user are reduced compared to classical geostatistical methods. These features present clear advantages for an automatic mapping system. The performance of the SSRF predictor is evaluated by means of various cross-validation measures. The values of the performance measures are similar to those obtained by classical geostatistical methods. Application of the SSRF method to data that simulate a radioactivity release scenario is also discussed. Hot spots are detected and removed using a heuristic method. The extreme values that appear in the path of the simulated plume are not captured by the currently used Spartan spatial model. Modeling of the processes leading to extreme values can enhance the predictive capabilities of the spatial model, by incorporating physical information.
Starting Page	633
Ending Page	646
Page Count	14
File Format	PDF
ISSN	14363240
Journal	Stochastic Environmental Research and Risk Assessment
Volume Number	22
Issue Number	5
e-ISSN	14363259
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-06-26
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Correlations Stochastic estimation Spatial interpolation Environmental monitoring Hot spots Radioactivity Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution Numerical and Computational Methods in Engineering Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences Probability Theory and Stochastic Processes Math. Applications in Geosciences Math. Application in Environmental Science
Content Type	Text
Resource Type	Article
Subject	Environmental Chemistry Environmental Engineering Water Science and Technology Safety, Risk, Reliability and Quality

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