Bibliography

Arulampalam2002
Arulampalam, M.S. and Maskell, S.. “A tutorial on particle filters for online nonlinear/non-Gaussian/Bayesian tracking”. 2002.
Doucet2001
Doucet, A., de Freitas, N., and Gordon, N.. “Sequential Monte Carlo Methods in Practice”. Springer. 2001.
Doucet2000
Doucet, A., Godsill, S., and Andrieu, C.. “On sequential Monte Carlo sampling methods for Bayesian filtering”. Statistics and Computing. 10. 197-208. 2000.
Evensen2003
Evensen, Geir. “The Ensemble Kalman Filter: theoretical formulation and practical implementation”. Ocean Dynamics. 53. 343-367. 2003.
Evensen1994
Evensen,G.. “Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics”. Journal of Geophysical Research. 99. 10143-10162. 1994.
Karssenberg2006
Karssenberg, D and De Jong, K.. “Towards improved solution schemes for Monte Carlo simulation in environmental modeling languages”. NCG Nederlandse Commissie voor Geodesie, Netherlands Geodetic Commission. 2006.
Karssenberg2005a
Karssenberg, D. and De Jong, K.. “Dynamic environmental modelling in GIS: 1. Modelling in three spatial dimensions”. International Journal of Geographical Information Science. 19. 559-579. 2005.
Karssenberg2005b
Karssenberg, D. and De Jong, K.. “Dynamic environmental modelling in GIS: 2. Modelling error propagation”. International Journal of Geographical Information Science. 19. 623-637. 2005.
Karssenberg2009
Karssenberg, D., Schmitz, O., De Vries, L.M., Bierkens, M. F. P., De Jong, K., and Salamon, P.. “A software framework for construction of stochastic spatio-temporal models assimilated or calibrated with observational data.”. in prep..
Simon2006
Simon, D.. “Optimal State Estimation: Kalman, H and Nonlinear Approaches”. Wiley-Interscience. 2006.
Weerts2006
Weerts, A. H. and El Serafy, G. Y. H.. “Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models”. Water Resources Research. 42. 2006.
Xiong2006
Xiong, X., Navon, I. M., and Uzunoglu, B.. “A note on the particle filter with posterior Gaussian resampling”. Tellus, Series A: Dynamic Meteorology and Oceanography. 58. 456-460. 2006.
Karssenberg2007:
Karssenberg, D., de Jong, K., and Van der Kwast, J.. “Modelling landscape dynamics with Python”. International Journal of Geographical Information Science. 2007.
pcraster2008
PCRaster . “PCRaster website”. http://pcraster.geo.uu.nl/. 2008.

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