Abida, R. and M. Bocquet, 2009 : Targeting of observations for accidental atmospheric release monitoring. Atmospheric Environment, 43, 6312-6327, doi :10.1016/j.atmosenv. 2009.09.029. Abida, R., M. Bocquet, N. Vercauteren, and O. Isnard, 2008 : Design of a monitoring network over france in case of a radiological accidental release. Atmospheric Environment, 42, 5205-5219, doi :10.1016/j.atmosenv.2008.02.065. Atkinson, A. C. and A. N. Donev, 1992 : Optimum experimental designs. Oxford University Press, Oxford. Audze, P. and V. Eglais, 1977 : New approach for planning out of experiments. Problems of Dynamics and Strengths, 35, 104-107. Banjevic, M. and P. Switzer, 2001 : Optimal network designs in spatial statistics. Royal Statistical Society Conference on Spatial Modelling, Glasgow. Bates, S., J. Sienz, and V. Toropov, 2004 : Formulation of the optimal latin hypercube design of experiments using a permutation genetic algorithm. AIAA 2004-2011, 1-7. Berliner, L. M., Z. Lu, and C. Snyder, 1999 : Statistical design for adaptive weather observations. J. Atmos. Sci, 56, 2536-2552. Bernardo, J. M., 1975 : Information theory and decision making. Theories of Decision in Practice, White, D. J, and Bowen, K. C (Eds). London : Hodder and Stoughton, 247-251. Bocquet, M., 2006-2009 : Construction optimale de réseaux de mesure : application à la suveillance des polluants aériens. notes de cours de l'École nationale supérieure des techniques avancées. Tech. rep., CEREA, École des Ponts ParisTech Université Paris-Est et INRIA. Boer, E. P. J., L. M. Dekkers, and A. Stein, 2002 : J. Environ. Qual., 31, 121-128. Brus, D. J. and G. B. M. Heuvelin, 2007 : Optimization of sample patterns for universal kriging of environmental variables. Geoderma, 138, 86-95. Bueso, M. C., J. M. Angulo, and F. J. Alonso, 1998 : A state-space model approach to optimum spatial sampling design based on entropy. Environmental and Ecological Statistics, 5, 29-44. Bueso, M. C., J. M. Angulo, F. J. Alonso, and M. D. Ruiz-Medina, 2005 : A study on sensitivity of spatial sampling designs to a priori discretization schemes. Environmental Modelling & Software, 20, 891-902. Caselton, W. and T. Husain, 1980 : Hydrologic networks : information transmission. J. Water Resources Planning and Management, 106, 503-529. Caselton, W. F., L. Kan, and J. V. Zidek, 1992 : Quality data networks that minimize entropy. Statistics in the Environmental and Earth Sciences, Walden, A. T, Guttorp, P., Eds. Edward Arnold, London. Caselton, W. F. and J. V. Zidek, 1984 : Optimal monitoring network designs. Stat. Prob. Lett, 2, 223-227. Cooper, J. R., K. Randle, and R. S. Sokhi, 2003 : Radioactive Releases in the Environment : Impact and Assessment. Hardcover. Cressie, N., 1993 : Statistics for spatial data. Wiley, New York. Cressie, N., C. A. Gotway, and M. O. Grondona, 1990 : Spatial prediction from networks. Chemometrics and Intelligent Laboratory Systems, 7, 251-271. Cressman, 1959 : An operational objective analysis system. Monthly Weather Rev, 87, 367-374. Di Zio, S., L. Fontanella, and L. Ippoliti, 200 : Optimal spatial sampling schemes for environmental surveys. Environmental and Ecological Statistics, 10, 397-414. Diggle, P. and S. Lophaven, 2006 : Bayesian geostatistical design. Scandinavian Journal of Statistics, 33, 55-64. Diggle, P. J., P. J. Ribeiro, and O. F. Christensen, 2003 : Spatial statistics and computational methods, chap. An introduction to model-based geostatistics, 43-86. Springer, New York. Drews, M., B. Lauritzen, H. Madsen, and J. Q. Smith, 2004 : Kalman filtration of radiation monitoring data from atmospheric dispersion of radioactive materials. Rad. Prot. Dos, 111, 257 - 269. Dubois, G., E. J. Pebesma, and P. Bossew, 2007 : Automatic mapping in emergency : a geostatistical perspective. International Journal of Emergency Management, 4, 455-467. Fedorov, V. V., 1972 : Theory of Optimal Experiments. Academic Press, New York. Fedorov, V. V., G. Montepiedra, and C. J. Nachtsheim, 1999 : Design of experiments for locally weighted regression. J. Stat. Plan. Inference, 81, 363-382. Fedorov, V. V. and W. G. Müller, 1988 : Two approaches in optimization of observing networks. Optimal Design and Analysis of Experiments, Dodge, Y., and Fedorov, V. V, and Wynn, H. P., New York, : North-Holland. Fedorov, V. V. and W. G. Müller, 1989 : Comparison of two approaches in the optimal design of an observation network'. Statistics, 20, 339-351. Ferreyra, R. A., H. P. Apezteguía, R. Sereno, and J. W. Jones, 2002 : Reduction of soil water spatial sampling density using scaled semivariograms and simulated annealing. Geoderma, 110, 265-289. Ferri, M. and M. Piccioni, 1992 : Optimal selection of statistical units : an approach via simulated annealing. Computational statistics and data analysis, 13, 47-61. Fuentes, M., A. Chaudhuri, and D. M. Holland, 2005 : Bayesian entropy for spatial sampling design of environmental data. Tech. rep., Institute of Statistics Mimeo Series No. 2571. Galmarini, S., R. Bianconi, G. de Vries, and R. Bellasio, 2008 : Real-time monitoring data for real-time multi-model validation : coupling ensemble and eurdep. Journal of Environmental Radioactivity, 99, 1233-1241. Gandin, L. S., 1963 : Objective analysis of meteorological fields. Gidrometeorologicheskoe Izdatel'stvo. Gastner, M. T. and M. E. J. Newman, 2006 : Optimal design of spatial distribution networks. Phys. Rev. E., 74. Guttorp, P., N. D. Le, P. D. Sampson, and J. V. Zidek, 1993 : Using entropy in the redesign of an environmental monitoring network. Multivariate Environmental Statistics, Eds, Patil, G. P., Rao, C. R., New York : North Holland/Elsevier Science, 175-202. Hughes-Oliver, J. M., G. Gonzalez-Faria, J. C. Lu, and D. Chen, 1998 : Parametric nonstationary spatial correlation models. Statistics and Probability Letters, 40, 267-278. IAEA, 1997 : Generic assessment procedures for determining protective actions during a reactor accident. Tech. rep., IAEATECDOC-955, IAEA Vienna. IAEA, 2002 : Preparedness and response for a nuclear or radiological emergency. safety requirements. Tech. rep., Safety Requirements, Safety Standards Series No. GS-R-2, IAEA Vienna. Janssens, A., F. Raes, and M. De Cort, 1993 : Off-site emergency response to nuclear accidents. Environmental Monitoring Peer Reviewed Journal. Joly, A., et al., 1997 : The fronts and atlantic storm-track experiment (fastex) : scientific objectives and experimental design. Bull. Am. Meteorol. Soc, 78, 1917-1940. Karhu, P., 2004 : Radionuclide monitoring as part of the verification regime for the comprehensive nuclear-test-ban treaty. Radiochemistry, 455-457. Kiefer, J., 1975 : Construction and optimality of generalized youden designs. A survey of Statistical Design and Linear Models, Srivastava, J. N (Ed), Amsterdam : North-Holland, 333-353. Kiefer, J. and J. Wolfowitz, 1960 : The equivalence of two extremum problems. Canadian Journal of Mathematics, 12, 363-366. Ko, C.-W., J. Lee, and M. Queyranne, 1995 : An exact algorithm for maximum entropy sampling. Operations Research, 43, 684-691. Krysta, M., M. Bocquet, B. Sportisse, and O. Isnard, 2006 : Data assimilation for shortrange dispersion of radionuclides : an application to wind tunnel data. Atmos. Env, 40, 7267-7279. Lauritzen, B. and U. B''averstam, 1999 : Probabilistic approach to derive operational intervention levels for nuclear emergency preparedness. Health Physics, 77. Lauritzen, B., P. H. Jensen, and F. Nielsen, 2005 : Requirements to a norwegian national automatic gamma monitoring system. Tech. rep., Risø National Laboratory : Risø-R- 1514. Le, N. D., L. Sun, and J. V. Zidek, 2003 : Designing networks for monitoring multivariate environmental fields using data with monotone pattern. Tech. rep., Statistical and Applied Mathematical Sciences Institute, RTP, NC. Le, N. D. and J. V. Zidek, 1994 : Network designs for monitoring multivariate random spatial fields. Recent. Adv. in Statist. and Prob, Eds., Vilaplana, J. P., Puri, M. L., 191-206. Lovejoy, S., D. Schertzer, and P. Ladoy, 1989 : Fractal characterization of inhomogeneous geophysical measuring networks. Nature, 319, 43 - 44. Makhon'ko, K. P., 1996 : Some results of radiation monitoring after the chernobyl accident. Radiation Protection Dosimetry, 64, 61-68. Mandelbrot, B. B., 1982 : The Fractal Geometry of Nature. W.H. Freeman and Company. Mardia, K. V., J. T. Kent, and J. M. Bibby, 1979 : Multivariate Analysis. Mason, L. R. and J. B. Bohlin, 1995 : Network optimization of a radionuclide monitoring system for the comprehensive nuclear test ban treaty. Tech. rep., Pacific-Sierra Research Corporation, PSR Technical Report 2585. Mathéron, G., 1963 : Principles of geostatistics. Economic Geology, 35, 1246-1266. MAZZOLDI, A., T. HILL, and J. J. CALLS, 2008 : Cfd and gaussian atmospheric dispersion models : A comparison for leak from carbon dioxide transportation and storage facilities. Atmospheric environment, 42, 8046-8054. Müller, W. G., 2007 : Collecting Spatial Data. Nunes, L. M., E. Paralta, M. C. Cunha, and L. Ribeiro, 2004 : Groundwater nitrate monitoring network optimization with missing data. Water Resour. Res, 40. Nychka, D. and N. Saltzman, 1998 : Design of air quality monitoring networks. Case studies in environmental statistics, Nychka, D., and Cox, L., and Piegorsch, W., Springer-Verlag. Pardo-Igúzquita, E., 1998 : Optimal selection of number and location of rainfall gauges for areal rainfall estimation using geostatistics and simulated annealing. J. Hydrol, 210, 206-220. Raes, F., M. De Cort, and G. Graziani, 1991 : The multi-fractal nature of radioactivity deposition on soil after the chernobyl accident. Health physics, 61, 271-274. Ramiro Ruiz, C. and A. R. F. Marco, 2009 : Stochastic search algorithms for optimal design of monitoring networks. Environmetrics. Reay, J. S. S. and D. T. Swift-Hook, 1979 : The philosophy of monitoring [and discussion]. Phil. Trans. of the Royal Soc A, 290, 609-623. Reed, P., B. Minsker, and A. J. Valocchi, 2000 : Cost-effective long-term groundwater monitoring design using a genetic algorithm and global mass interpolation. Water Resour. Res, 36, 3731-3741. Rojas-Palma, C., et al., 2003 : Data assimilation in the decision support system rodos. Rad. Prot Dos, 104, 31-40. Royle, J. A. and D. Nychka, 1997 : An algorithm for the construction of spatial designs with an implementation in splus. Computers and Geosciences, 24, 479-488. Saunier, O. and M. Bocquet, 2009 : Model reduction via principal component truncation for the optimal design of atmospheric monitoring networks. Atmospheric Environment, 43, 4940-4950. Silvey, S. D., 1980 : Optimal design. Chapman and Hall, London. Stein, M. L., 1999 : Interpolation of Spatial Data : Some Theory for Kriging. Springer, New York. Tibshirani, R., 1996 : Regression shrinkage and selection via the lasso. J. Royal. Statist. Soc B., 58, 267-288. Trujillo-Ventura, A. and J. H. Ellis, 1991 : Multiobjective air pollution monitoring network design. Atmospheric Environment, 25, 469-479. Van Groenigen, J. and A. Stein, 1998 : Constrained optimisation of spatial sampling, a geostatistical approach. J. Environ. Qual, 27, 1078-1086. Warrick, A. W. and D. E. Myers, 1987 : Optimization of sampling locations for variogram calculations. Water Resources Research, 23, 496-500. Wu, J., C. Zheng, and C. C. Chien, 2005 : Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions. Journal of Contaminant Hydrology, 77, 41-65. Wu, L. and M. Bocquet, 2009 : Optimal reduction of the ozone monitoring network over france. submitted to Atmospheric Chemistry and Physics. Wu, S. and J. V. Zidek, 1992 : An entropy-based analysis of data from selected nadp/ntn network sites for 1983-1986. Atmospheric Environment : Part A, 26, 2089-2103. Zannetti, P., 1990 : Air pollution modeling : theories, computational methods, and available software. Van Nostrand Reinhold, New York. Zidek, J. V., W. Sun, and N. D. Le, 2000 : Designing and integrating composite networks for monitoring multivariate (gaussian) pollution fields. Journal of Applied Statistics, 49, 63-79. |