Spatial extrapolation of anisotropic road traffic data

Image Analysis and Stereology

Volumn 23, Issue 3, 2004, Pages 185-198

  Braxmeier, Hans ^a   Schmidt, Volker ^a   Spodarev, Evgueni ^a  

^a UNIVERSITY OF ULM   (Germany)

Author keywords

Anisotropy; Asymptotic gaussian test; Boolean model; Kriging; Moving neighborhood; Random field

Indexed keywords

EID: 78650428683     PISSN: 15803139     EISSN: 18545165     Source Type: Journal    
DOI: 10.5566/ias.v23.p185-198     Document Type: Article

References (26)

1. Bohm S, Heinrich L, Schmidt V (2004). Asymptotic properties of estimators for the volume fraction of jointly stationary random sets. Statistica Neerlandica, 58:1-19.
2. Chiles JP, Delfiner P (1999). Geostatistics: modelling spatial uncertainty. New York: Wiley.
3. Cressie NAC (1993). Statistics for spatial data. New York: Wiley.
4. Faulkner B (2002). Java classes for nonprocedural variogram modelling. Comput Geosci 28(3):387-97.
5. Genton MG (1998a). Highly robust variogram estimation. Math Geol 30:213-21.
6. Genton MG (1998b). Variogram fitting by generalized least squares using an explicit formula for the covariance structure. Math Geol 30:323-45.
7. Genton MG (2001). Robustness problems in the analysis of spatial data. In: Moore M, ed. Spatial Statistics: Methodological Aspects and Applications. Lecture Notes in Statistics. New York: Springer, 21-37.
8. GeoStoch (2004). Java library. University of Ulm, Department of Applied Information Processing and Department of Stochastics, http://www.geostoch.de/.
9. Goldberg DE (1989). Genetic algorithms in search, optimization, and machine learning. Boston: Addison-Wesley.
10. Heinrich L, Schmidt H, Schmidt V (2004). Limit theorems for stationary tessellations with random inner cell structures. Adv Appl Probab (to appear).
11. Kitanidis PK (1997). Introduction to geostatistics: applications to hydrogeology. New York: Cambridge University Press.
12. Klenk S, Schmidt V, Spodarev E (2004). A new algorithmic approach to the computation of Minkowski functionals of polyconvex sets. Preprint (submitted).
13. Lantuejoul C (2002). Geostatistical simulation: models and algorithms. Berlin: Springer.
14. Lehmann E, Casella G (1998). Theory of point estimation, 2nd edition. New York: Springer.
15. Mayer J, Schmidt V, Schweiggert F (2004). A unified simulation framework for spatial stochastic models. Simul Model Pract Th 12:307-26.
16. Megnin C (2001). Jsimul: a Java-based simulated annealing package. http://www.theblueplanet.org/JSimul/html/JSimul_readme.html.
17. Niemeyer P, Peck J (1996). Exploring Java. Bonn: O'Reilly.
18. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (2002). Numerical recipes in C++. The art of scientific computing, 2nd edition. Cambridge, Mass.: Cambridge University Press.
19. Schmidt V, Spodarev E (2004). Joint estimators for the specific intrinsic volumes of stationary random sets. Stoch Proc Appl (to appear).
20. Segewick R (1992). Algorithmen in C. Bonn: Addison-Wesley.
21. Serra J (1988). Image analysis and mathematical morphology: theoretical advances, volume 2. London: Academic Press.
22. Stoyan D, Stoyan H, Jansen U (1997). Umweltstatistik. Stuttgart: Teubner.
23. Stoyan D, Kendall WS, Mecke J (1995). Stochastic geometry and its applications, 2nd edition. Chichester: Wiley.
24. Tomasi C, Manduchi R (1998). Bilateral filtering for gray and color images. In: Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India, 839-46.
25. Wackernagel H (1998). Multivariate geostatistics, 2nd edition. Berlin: Springer.
26. zu Castell W, Weller U, Zipprich M, Sommer M, Wehrhan M (2002). Kriging considered from the deterministic point of view. In: Bayer U, Burger H, and Skala W, eds. Terra Nostra. Schriften der Alfred-Wegener-Stiftung, volume 3, Berlin, 249-54.