Landscape Ecology

, Volume 11, Issue 1, pp 39–49 | Cite as

Effects of changing spatial resolution on the results of landscape pattern analysis using spatial autocorrelation indices



Understanding the relationship between pattern and scale is a central issue in landscape ecology. Pattern analysis is necessarily a critical step to achieve this understanding. Pattern and scale are inseparable in theory and in reality. Pattern occurs on different scales, and scale affects pattern to be observed. The objective of our study is to investigate how changing scale might affect the results of landscape pattern analysis using three commonly adopted spatial autocorrelation indices,i.e., Moran Coefficient, Geary Ratio, and Cliff-Ord statistic. The data sets used in this study are spatially referenced digital data sets of topography and biomass in 1972 of Peninsular Malaysia. Our results show that all three autocorrelation indices were scale-dependent. In other words, the degree of spatial autocorrelation measured by these indices vary with the spatial scale on which analysis was performed. While all the data sets show a positive spatial autocorrelation across a range of scales, Moran coefficient and Cliff-Ord statistic decrease and Geary Ratio increases with increasing grain size, indicating an overall decline in the degree of spatial autocorrelation with scale. The effect of changing scale varies in their magnitude and rate of change when different types of landscape data are used. We have also explored why this could happen by examining the formulation of the Moran coefficient. The pattern of change in spatial autocorrelation with scale exhibits threshold behavior,i.e., scale effects fade away after certain spatial scales are reached (for elevation). We recommend that multiple methods be used for pattern analysis whenever feasible, and that scale effects must be taken into account in all spatial analysis.


landscape patterns spatial analysis spatial autocorrelation scale effect grain size Moran Coefficient Geary Ratio Cliff-Ord statistic 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allen, T.F.H. and Starr, T.B. 1982. Hierarchy: Perspectives for Ecological Complexity. University of Chicago Press, Chicago.Google Scholar
  2. Burgess, R.L. and Sharpe, D.M. (eds). 1981. Forest Island Dynamics in Man-Dominated Landscapes. Springer-Verlag, New York.Google Scholar
  3. Brown, S., Iverson, L.R. and Lugo, A.E. 1994. Land use and biomass changes of forests in Peninsular Malaysia during 1972–1982: use of GIS analysis.In Effects of Land-Use Change on Atmospheric CO2 Concentrations: Southeast Asia as a Case Study, pp. 117–143. Edited by V. Dale. Springer-Verlag, New York.Google Scholar
  4. Cliff, A. and Ord, J.K. 1973. Spatial Autocorrelation. Pion, London.Google Scholar
  5. Cliff, A. and Ord, J.K. 1981. Spatial Process. Pion, London.Google Scholar
  6. Costanza, R. and Maxwell, T. 1994. Resolution and predictability: An approach to the scaling problem. Landsc. Ecol. 9: 47–57.CrossRefGoogle Scholar
  7. Cullinan, V.I. and Thomas, J.M. 1992. A comparison of quantitative methods for examining landscape pattern and scale. Landsc. Ecol. 7: 211–227.CrossRefGoogle Scholar
  8. Forman, R.T.T. and Godron, M. 1986. Landscape ecology. Wiley, New York.Google Scholar
  9. Fortin, M.-J., Drapeau, P. and Legendre, P. 1989. Spatial autocorrelation and sampling design in plant ecology. Vegetatio 83: 209–222.CrossRefGoogle Scholar
  10. Getis, A. and Boots, B. 1978. Models of spatial processes: an approach to the study of point, line and area patterns. Cambridge University Press, Cambridge, England.Google Scholar
  11. Getis, A. and Ord, J.K. 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis 24: 189–206.Google Scholar
  12. Goodchild, M.F. 1986. Spatial Autocorrelation. Concepts and Techniques in Modern Geography 47, Geo Books, Norwich.Google Scholar
  13. Greig-Smith, P. 1952. The use of random and contiguous quadrats in the study of the structure of plant communities. Ann. Bot., New Series 16: 293–316.Google Scholar
  14. Griffith, D.A. 1988. Advanced Spatial Statistics. Special Topics in the Exploration of Quantitative Spatial Data Series. Kluwer Academic Publishers, Dordrecht.Google Scholar
  15. Griffith, D.A. 1990. Supercomputing and spatial statistics: A reconnaissance. Prof. Geogr. 42(4): 481–492.CrossRefGoogle Scholar
  16. Kershaw, K.A. 1957. The use of cover and frequency in the detection of pattern in plant communities. Ecology 38: 291–299.Google Scholar
  17. Legendre, P. 1993. Spatial autocorrelation: trouble or new paradigm? Ecology 74: 1659–1673.Google Scholar
  18. Legendre, P. and Fortin, M. J. 1989. Spatial pattern and ecological analysis. Vegetatio 80: 107–138.CrossRefGoogle Scholar
  19. Levin, S.A. 1992. The problem of pattern and scale in ecology. Ecology 73: 1943–1967.Google Scholar
  20. Levin, S.A., Powell, T. and Steele, J.H. (eds.) 1993. Patch Dynamics. Springer-Verlag, New York.Google Scholar
  21. Meentemeyer, V. and Box, E.O. 1987. Scale effects in landscape studies.In Landscape Heterogeneity and Disturbance. pp. 15–34. Edited by M.G. Turner. Springer-Verlag, New York.Google Scholar
  22. Milne, B.T. 1988. Measuring the fractal geometry of landscapes. Appl. Math. Comp. 27: 67–79.CrossRefGoogle Scholar
  23. Morris, D.W. 1987. Ecological scale and habitat use. Ecology 68: 362–369.Google Scholar
  24. Nellis, M.D. and Briggs, J.M. 1989. The effect of spatial scale on Konza landscape classification using textural analysis. Landsc. Ecol. 3: 93–100.CrossRefGoogle Scholar
  25. Odland, J. Spatial Autocorrelation. SAGE Publications, Newbury Park.Google Scholar
  26. O'Neill, R.V., DeAngelis, D.L., Waide, J.B. and Allen, T.F.H. 1986. A Hierarchical Concept of Ecosystems. Princeton University Press, Princeton.Google Scholar
  27. O'Neill, R.V., Krummel, J.R., Gardner, R.H., Sugihara, G., Jackson, B., DeAngelis, D.L., Milne, B.T., Turner, M.G., Zygmunt, B., Chistensen, S., Dale, V.H. and Graham, R.L. 1988. Indices of landscape pattern. Landsc. Ecol. 1: 153–162.CrossRefGoogle Scholar
  28. Opdam, P. 1991. Metapopulation theory and habitat fragmentation: A review of holarctic breeding bird studies. Landsc. Ecol. 5: 93–106.CrossRefGoogle Scholar
  29. Risser, P.G., Karr, J.R. and Forman, R.T.T. 1984. Landscape Ecology: Directions and Approaches. Illinois Natural History Survey, Special Publication Number 2.Google Scholar
  30. Turner, M.G., Dale, V.H. and Gardner, R.H. 1989. Predicting across scales: theory development and testing. Landsc. Ecol. 3: 245–252.CrossRefGoogle Scholar
  31. Turner, M.G. and Gardner, R.H. (eds). 1991. Quantitative Methods in Landscape Ecology. Springer-Verlag, New York.Google Scholar
  32. Turner, M.G., O'Neill, R.V., Gardner, R.H. and Milne, B.T. 1989. Effects of changing spatial scale on the analysis of landscape pattern. Landsc. Ecol. 3: 153–162.CrossRefGoogle Scholar
  33. Wiens, J.A. and Milne, B.T. 1989. Scaling of “landscape” in landscape ecology, or, landscape ecology from a beetle's perspective. Landsc. Ecol. 3: 87–96.CrossRefGoogle Scholar
  34. Wiens, J.A., Stenseth, N.C., Horne, B. van and Ims, R.A. 1993. Ecological mechanisms and landscape ecology. Oikos 66: 369–380.Google Scholar
  35. Wu, J. 1992a. Detecting spatial patterns: the net-function interpolation. Coenoses 7(3): 137–143.Google Scholar
  36. Wu, J. 1992b. Balance of nature and environmental protection: A paradigm shift. Proc. 4th Intern. Conf. Asia Experts. Portland State University, Portland, OR, May 7–8, 1992.Google Scholar
  37. Wu, J., Jelinski, D. and Qi, Y. 1994. Spatial pattern analysis of a boreal forest landscape: Scale effects and interpretation.Proc. VI Intern. Conf. Ecology (INTECOL), pp. 165. Univ. of Manchester, Manchester, August 21–26, 1994.Google Scholar
  38. Wu, J. and Levin, S.A. 1994. A spatial patch dynamic modeling approach to pattern and process in an annual grassland. Ecol. Monogr. 64(4): 447–464.Google Scholar
  39. Wu, J., Li, B. and Wu, Y. 1992. Patchiness and patch dynamics: I. Concepts and mechanisms. Chin. J. Ecol. 11(4): 41–45.Google Scholar
  40. Wu, J. and Vankat, J.L. 1991a. A system dynamics model of island biogeography. Bull. Math. Biol. 53: 911–930.CrossRefGoogle Scholar
  41. Wu, J. and Vankat, J.L. 1991b. An area-based model of species richness dynamics of forest islands. Ecol. Modell. 58: 249–271.CrossRefGoogle Scholar
  42. Wu, J. and Vankat, J.L. 1995. Island biogeography: Theory and applications.In Encyclopedia of Environmental Biology. Edited by W.A. Nierenberg: Academic Press (in press).Google Scholar
  43. Wu, J., Vankat, J.L. and Barlas, B. 1993. Effects of patch connectivity and arrangement on animal metapopulation dynamics: a simulation study. Ecol. Modell. 65: 221–254.CrossRefGoogle Scholar
  44. Zonneveld, I.S. and Forman, R.T.T. (eds). 1990. Changing Landscapes: An Ecological Perspective. Springer-Verlag, New York.Google Scholar

Copyright information

© SBP Academic Publishing bv 1996

Authors and Affiliations

  1. 1.Scripps Institution of OceanographyUniversity of California at San DiegoLa JollaUSA
  2. 2.Biological Sciences Center, Desert Research InstituteUniversity of Nevada SystemRenoUSA

Personalised recommendations