Skip to main content
SpringerLink
Log in

The modifiable areal unit problem and implications for landscape ecology

  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

Landscape ecologists often deal with aggregated data and multiscaled spatial phenomena. Recognizing the sensitivity of the results of spatial analyses to the definition of units for which data are collected is critical to characterizing landscapes with minimal bias and avoidance of spurious relationships. We introduce and examine the effect of data aggregation on analysis of landscape structure as exemplified through what has become known, in the statistical and geographical literature, as theModifiable Areal Unit Problem (MAUP). The MAUP applies to two separate, but interrelated, problems with spatial data analysis. The first is the “scale problem”, where the same set of areal data is aggregated into several sets of larger areal units, with each combination leading to different data values and inferences. The second aspect of the MAUP is the “zoning problem”, where a given set of areal units is recombined into zones that are of the same size but located differently, again resulting in variation in data values and, consequently, different conclusions. We conduct a series of spatial autocorrelation analyses based on NDVI (Normalized Difference Vegetation Index) to demonstrate how the MAUP may affect the results of landscape analysis. We conclude with a discussion of the broader-scale implications for the MAUP in landscape ecology and suggest approaches for dealing with this issue.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Allen, T.F.H. and Starr, T.B. 1982. Hierarchy. University of Chicago Press, Chicago.

    Google Scholar 

  • Amrhein, C. and Flowerdew, R. 1989. The effect of data aggregation on a Poisson regression model of Canadian migration.In: Accuracy of Spatial Databases. pp. 229–238. Edited by M.F. Goodchild and S. Gopal, Taylor and Francis, London.

    Google Scholar 

  • Box, E., Holben, B.N. and Kalb, V. 1989. Accuracy of the AVHRR vegetation index as a predictor of biomass, primary productivity and net CO2 flux. Vegetation 80: 71–89.

    Article  Google Scholar 

  • Burke, I.C., Kittel, T.G.F., Lauenroth, W.K., Snook, P., Yonker, C.M. and Parton, W.J. 1991. Regional analysis of the Great Plains. BioScience 25: 685–692.

    Article  Google Scholar 

  • Cliff, A.D. and Ord, J.K. 1973. Spatial Autocorrelation. Pion, London.

    Google Scholar 

  • Cressie, N.A.C. 1993. Statistics for Spatial Data. J. Wiley, New York.

    Google Scholar 

  • Cullinan, V.I. and Thomas, J.M. 1992. A comparison of quantitative methods for examining landscape pattern and scale. Landscape Ecology 7: 211.

    Article  Google Scholar 

  • DeAngelis, D.L. and Gross, L.J. (eds.) 1992. Individual-Based Models and Approaches in Ecology: Populations, Communities and Ecosystems. Chapman & Hall, New York.

    Google Scholar 

  • DeAngelis, D.L. and Waterhouse, J.C. 1987. Equilibrium and nonequilibrium concepts in ecological models. Ecological Monographs 57: 1–21.

    Article  Google Scholar 

  • Elliott-Fisk, D.L. The Boreal Forest. In North American Terrestrial Vegetation, pp. 33–62. Edited by M.G. Barbour and W.D. Billings. Cambridge University Press, Cambridge.

  • Errington, J.C. 1973. The effect of regular and random distributions on the analysis of pattern. Journal of Ecology 61: 99–105.

    Article  Google Scholar 

  • Forman, R.T.T. and Godron, M. 1986. Landscape Ecology. John Riley & Sons, New York.

    Google Scholar 

  • Fotheringham, A.S., 1989. Scale-independent spatial analysis.In: Accuracy of Spatial Databases, pp. 221–228. Edited by M.F. Goodchild and S. Gopal. Taylor and Francis, London.

    Google Scholar 

  • Fotheringham, A.S., and Rogerson, P.A. 1993. GIS and spatial analytical problems. International Journal of Geographic Information Systems 7: 3–19.

    Google Scholar 

  • Fotheringham, A.S., and Wong, D.W.S. 1991. the modifiable areal unit problem in statistical analysis. Environment and Planning A 23: 1025–1044.

    Google Scholar 

  • Gardner, R.H., Cale, W.G. and O'Neill, R.V. 1982. Robust analysis of aggregation error. Ecology 63: 1771–1779.

    Article  Google Scholar 

  • Greig-Smith, P. 1952. The use of random and contiguous quadrats in the study of the structure of plant communities. Annals of Botany, New Series 16: 293–316.

    Google Scholar 

  • Greig-Smith, P. 1957. Quantitative Plant Ecology. Academic Press, New York.

    Google Scholar 

  • Greig-Smith, P. 1979. Pattern in vegetation. Journal of Ecology. 67: 755–779.

    Article  Google Scholar 

  • Greig-Smith, P. 1983. Quantitative Plant Ecology, 3rd ed. University of California Press, Berkeley.

    Google Scholar 

  • Hall, F.G., Strebel, D.E. and Sellers, P.J. 1988. Linking knowledge among spatial and temporal scales: Vegetation, atmosphere, climate and remote sensing. Landscape Ecology 2: 3–22.

    Article  Google Scholar 

  • Jelinski, D.E., Goodchild, M. and Steyaert, L. 1994. Multiple roles for GIS in global change research: towards a research agenda.In: Environmental Information Management and Analysis: Ecosystem to Global Scales. pp. 41–56. Edited by W.K. Michener, J.W. Brunt and S.G. Stafford, Taylor & Francis, London.

    Google Scholar 

  • Johnson, D.D. and Howarth, P.J. 1987. The effects of spatial resolution on land cover/land use theme extraction from airborne digital data. Canadian Journal of Remote Sensing 13: 68–74.

    Google Scholar 

  • Kershaw, K.A. 1957. The use of cover and frequency in the detection of pattern in plant communities. Ecology 38: 291–299.

    Article  Google Scholar 

  • Kershaw, K.A. 1964. Quantitative and Dynamic Ecology. Edward Arnold, London.

    Google Scholar 

  • Legendre, P. and Fortin, M.-J.F. 1989. Spatial pattern and ecological analysis. Vegetatio 80: 107–138.

    Article  Google Scholar 

  • Levin, S.A. 1992. The problem of pattern and scale in ecology. Ecology 73: 1943–1967.

    Article  Google Scholar 

  • Levin, S.A. 1993. Concepts of scale at the local level.In: Scaling Physiological Processes: Leaf to Globe. pp. 7–19. Edited by J.R. Ebleringer and C.B. Field. Academic Press, San Diego, California.

    Google Scholar 

  • Loveland, T.R., Merchant, J.W., Ohlen, D.O. and Brown, J.F. 1991. Development of a landcover characteristics database for the conterminous U.S. Photogrammetric Engineering and Remote Sensing 57: 1453–1463.

    Google Scholar 

  • Meentemeyer, V. 1989. Geographical perspectives of space, time, and scale. Landscape Ecology 3: 163–173.

    Article  Google Scholar 

  • Milne, B.T. 1988. Measuring the fractal geometry of landscapes. Applied Mathematics and Computing 27: 67–79.

    Article  Google Scholar 

  • Nellis, M.D. and Briggs, J.M. 1989. The effect of spatial scale on Konza landscape classification using textural analysis. Landscape Ecology 2: 93–100.

    Article  Google Scholar 

  • 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, New Jersey.

    Google Scholar 

  • Openshaw, S. 1977. Optimal zoning systems for spatial interaction models. Environment and Planning A: 169–184.

    Google Scholar 

  • Openshaw, S. 1984. The modifiable areal unit problem. CATMOG 38. GeoBooks, Norwich, England.

    Google Scholar 

  • Openshaw, S. and Taylor, P. 1979. A million or so correlation coefficients: three experiments on the modifiable areal unit problem.In: Statistical Applications in the Spatial Sciences. pp. 127–144. Edited by N. Wrigley. Pion, London.

    Google Scholar 

  • Openshaw, S. and Taylor, P.J. 1981. The modifiable areal unit problem.In: Quantitative Geography: A British View. pp. 60–69. Edited by N. Wrigley and R. Bennett. Routledge and Kegan Paul, London.

    Google Scholar 

  • Openshaw, S., Charlton, M., Wymer, C. and Craft, A. 1987. Mark I geographical analysis machine for the automated analysis of point data sets. International Journal of Geographic Information Systems 1: 35–51.

    Google Scholar 

  • Openshaw, S., Charlton, M. and Craft, A. 1988. Searching for Leukemia clusters using a geographical analysis machine. Papers of the Regional Science Association 64: 95–106.

    Google Scholar 

  • Gehlke, C.E. and Biehl, K. 1934. Certain effects of grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association Supplement 29: 169–170.

    Article  Google Scholar 

  • Pacala, S.W. and Silander Jr., J.A. 1985. Neighborhood models of plant population dynamics: I. Single-species models of annuals. American Naturalist 125: 385–411.

    Article  Google Scholar 

  • Putnam, S.H. and Chung, S.-H. 1989. Effects of spatial system design on spatial interaction models. 1: The spatial system definition problem. Environment of Planning A 21: 27–46.

    Google Scholar 

  • Rastetter, E.B., King, A.W., Cosby, B.J., Hornberger, G.M., O'Neill, R.V. and Hobbie, J.E. 1992. Aggregating fine-scale ecological knowledge to model coarser-scale attributes of ecosystems. Ecological Applications 2: 55–70.

    Article  Google Scholar 

  • Robinson, A.H. 1950. Ecological correlation and the behaviour of individuals. American Sociological Review 15: 351–357.

    Article  Google Scholar 

  • Rosswall, T., Woodmansee, R.G. and Risser, P.G., editors. 1988. Scales and Global Change. John Wiley & Sons, New York.

    Google Scholar 

  • Roughgarden, J., Running, S.W. and Matson, P.A. 1991. What does remote sensing do for ecology? Ecology 72: 4: 45–54

    Google Scholar 

  • Taylor, P.J. and Johnston, R.J. 1979. Geography of Elections. Penguin, Harmondsworth.

    Google Scholar 

  • Tobler, W.R. 1989. Frame independent spatial analysis.In: Accuracy of Spatial Databases, pp. 115–122. Edited by M.F. Goodchild and S. Gopal Taylor and Francis, London.

    Google Scholar 

  • Townshend, J.R.G. and Justice, C.O. 1990. The spatial variation of vegetation changes at very coarse scales. International Journal of Remote Sensing 11: 149–157.

    Google Scholar 

  • Turner, M.G., Dale, V.H. and Gardner, R.H. 1989. Predicting across scales: theory development and testing. Landscape Ecology 3: 235–252.

    Google Scholar 

  • Turner, S.J., O'Neill, R.V., Conley, W., Conley, M.R. and Humphries, H.C. 1981. Pattern and scale: Statistics for landscape ecology.In: Quantitative Methods in Landscape ecology: The Analysis and Interpretation of Landscape Heterogeneity. pp. 17–49. Edited by M.G. Turner and R.H. Gardner. Springer-Verlag, New York.

    Google Scholar 

  • 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. Landscape Ecology 3: 153–162.

    Article  Google Scholar 

  • Upton, G.J.G. and Fingleton, B. 1985. Spatial data Analysis by Example. Volume 1: Point Pattern and Quantitative Data. John Wiley & Sons, Chichester.

    Google Scholar 

  • Urban, D.L., O'Neill, R.V. and Shugart, H.H., Landscape ecology. BioScience 37: 119–127.

  • Usher, M.B. 1975. Analysis of pattern in real and artificial plant populations. Journal of Ecology 63: 569–586.

    Article  Google Scholar 

  • Wiens, J.A. and Milne, B.T. 1989. Scaling of “landscapes” in landscape ecology, or, landscape ecology from a beetle's perspective. Landscape Ecology 3: 87–96.

    Article  Google Scholar 

  • Wiens, J.A., Stenseth, N.C., Van Horne, B. and Ims, R.A. 1993. Ecological mechanisms and landscape ecology. Oikos 66: 369–380.

    Google Scholar 

  • Williams, E. and Jelinski, D.E. 1995. On using the NOAA AVHRR “Experimental Calibrated Biweekly Global Vegetation Index”. in press Photogrammetric Engineering and Remote Sensing.

  • Woodcock, C.E. and Strahler, A.H. 1987. The factor of scale in remote sensing. Remote Sensing of Environment 21: 311–332.

    Article  Google Scholar 

  • Wu, J. 1992. Detecting spatial patterns: the net-function interpolation. Coenoses 7: 137–143.

    CAS  Google Scholar 

  • Wu, J. and Levin, S.A. 1994. A spatial patch dynamic modeling approach to pattern and process in an annual grassland. Ecological Monographs 64: 447–467.

    Article  Google Scholar 

  • Wu, J. and Loucks, O.L. 1995. From balance-of-nature to hierarchical path dynamics: a paradigm shift in ecology. Quarterly Review of Biology (in press).

  • Yule, G. and Kendall, M. 1950. An introduction to the theory of statistics. Charles Griffin and Company Limited, New York, New York, USA.

    Google Scholar 

Download references

Author information

Author notes

  1. Jianguo Wu

    Present address: Department of Life Sciences, Arizona State University West, 4701 West Thunderbird Road, 85069-7100, Phoenix, AZ, USA

Authors and Affiliations

  1. Department of Forestry, Fisheries and Wildlife, Institute of Agriculture and Natural Resources, University of Nebraska Lincoln, 101 Plant Industry, 68583-0814, Lincoln, NE, USA

    Dennis E. Jelinski & Jianguo Wu

Authors
  1. Dennis E. Jelinski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianguo Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jelinski, D.E., Wu, J. The modifiable areal unit problem and implications for landscape ecology. Landscape Ecol 11, 129–140 (1996). https://doi.org/10.1007/BF02447512

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02447512

Keywords

Search

Navigation