This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bartlett M.S. 1960. Stochastic population models. Methuen and Co., London.
Beran J. 1994. Statistics for Long-Memory Processes. Chapman and Hall, New York.
Beran J. and Ghosh S. 1998. Root-n-consistent estimation in partial linear models with long-memory errors. Scandinavian Journal of Statistics 25: 345-357.
Beran J. and Ocker D. 1999. SEMIFAR forecasts, with applications to foreign exchange rates. Journal of Statistical Planning and Inference 80: 137-153.
Berger J.O. 1999. Statistical decision theory and Bayesian statistics. Springer Verlag, New York.
Bramson M., Cox J.T. and Durrett R. 1996. Spatial models for species area curves. Annals of Probability 24: 1727-1751.
Cliff A.D. and Ord J.K. 1981. Spatial processes: Models and applications. Pion Corp., London.
Cox D.R. and Hinkley D.V. 2000. Theoretical statistics. Chapman and Hall, New York.
Cox D.R. and Isham V. 1988. Point processes, Chapman and Hall, New York.
Cressie N.A.C. 1993. Statistics for spatial data. Wiley, New York.
Diggle P.J. 2003. Statistical analysis of spatial point patterns. Arnold, London.
Diggle P.J., Liang K.Y. and Zeger S.L. 1994. Analysis of longitudinal data. Oxford University Press, Oxford.
Dietrich M. 1997. Häufigkeit, Diversität,Verbreitung und Dynamik von epiphytischen Flechten in Schweizerischen Mittelland und den Voralpen. Inauguraldissertation der Philosophisch-natur-wissenschaftlichen Fakultät der Universität Bern.
Draghicescu D. 2002. Nonparametric quantile estimation for dependent data. Ph.D. thesis no. 2592, EPFL.
Eubank R. 1988. Spline smoothing and nonparametric regression. Marcel Dekker, New York.
Fan J. and Gijbels I. 1996. Local polynomial modeling and its applications. Chapman and Hall, London.
Foster B.L. and Tilman D. 2000. Dynamic and static views of succession: testing the descriptive power of the chronosequence approach. Plant Ecology 146: 1-10.
Ghosh S. 2001. Nonparametric trend estimation in replicated time series. Journal of Statistical Planning and Inference 97: 263-274.
Ghosh S. 2005. Random fields based explanation for power-laws in species-area curves. (Preprint).
Ghosh S., Dietrich M. and Scheidegger C. 1997a. Bootstrap based species-area curve estimation for epiphytic lichens in Switzerland. (Preprint; appears in the PhD thesis of the second author, University of Bern).
Ghosh S. and Draghicescu D. 2002. Predicting the distribution function for long-memory processes. International Journal of Forecasting 18: 283-290.
Ghosh S., Landmann G., Pierrat J.C. and Müller-Edzards C. 1997b. Spatio-temporal variation in defoliation. In: Müller-Edzards C., De Vries W. and Erisman J.W. (eds.). 10 years forest condi-tion monitoring in Europe. Studies on temporal development, spatial distribution, and impacts of natural and anthropogenic stress factors. pp. 35-50. Geneva and Brussels, United Nations Economic Commission for Europe /European Commission.
Ghosh S., Beran J., Heiler S., Percival D. and Tinner W. 2007. Memory, non-stationarity and trend: analysis of environmental time series. In: Kienast F., Wildi O. and Ghosh S. (eds.). A Changing World. Challenges for Landscape Research, Vol. 8: 223-247. Springer Landscape Series, Dordrecht.
Hampel F.R. 1987. Data analysis and self-similar processes. Proceedings of the 42nd session of the ISI, Tokyo, Book 4, 235-254.
Künsch H. 1986. Statistical aspects of self-similar processes. Invited paper, Proceedings of the first world congress of the Bernoulli society, Tashkent, vol. 1, Prohorov Yu. and Sazonov V.V. (eds). VNU Science press, Utrecht, 67-74.
Mandelbrot B.B. and Wallis J.R. 1968. Noah, Joseph and operational hydrology. Water Resources Res. 4: 909-918.
Mardia K.V. 1972. Statistics of directional data. Academic Press, London.
Matheron G. 1962. Traité de Géostatistique Appliquée. Cambridge Philosophical Society, Tome 1, Technip, Paris.
Matheron G. 1973. The intrinsic random functions and their applications. Advances in Applied Probability 5: 439-468.
Mingoti S.A. and Meeden G. 1992. Estimating the total number of distinct species using presence and absence data. Biometrics 48: 863-875.
Nychka D. 2000. Challenges in understanding the atmosphere. Journal of the American Statistical Association 95: 972-975.
Pickett T.A. 1989. Space-for-time substitution as an alternative to long-term studies. In: Likens E. (ed.). Long-Term Studies in Ecology: approaches and alternatives. Springer, New York. pp. 110-135.
Ripley B.D. 1988. Statistical inference for spatial processes. Cambridge University Press, Cambridge, UK.
Silverman B.W. 1986. Density estimation. Chapman a and Hall, London.
Smith E.P. and van Belle G. 1984. Nonparametric estimation of species richness. Biometrics 40: 119-129.
Vicsek T. 1992. Fractal growth phenomena. World Scientific cop., Singapore.
Wikle C.K., Milliff R.F., Nychka D. and Berliner L.M. 2001. Spatiotemporal hierarchical Bayesian modeling: tropical ocean surface winds. Journal of the American Statistical Association 96: 382-397.
Wildi O. 2002. Modelling succession from pasture to forest in time and space. Community Ecology 3: 181-189.
Wildi O. and Schütz M. 2000. Reconstruction of a long-term recovery process from pasture to forest. Community Ecology 1: 25-32.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer
About this chapter
Cite this chapter
Ghosh, S., Wildi, O. (2007). Statistical Analysis of Landscape Data: Space-for-time, Probability Surfaces and Discovering Species. In: Kienast, F., Wildi, O., Ghosh, S. (eds) A Changing World. Landscape Series, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4436-6_14
Download citation
DOI: https://doi.org/10.1007/978-1-4020-4436-6_14
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-4434-2
Online ISBN: 978-1-4020-4436-6
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)