Landscape Ecology

, Volume 22, Issue 1, pp 7–13 | Cite as

Effects of thematic resolution on landscape pattern analysis

  • Alexander Buyantuyev
  • Jianguo Wu


The thematic resolution of mapped data determines the amount of detail of geospatial information, and influences various aspects of landscape classification and the relevance of derived pattern attributes to particular ecological questions. Here we show that changing thematic resolution may significantly affect landscape metrics and in turn their ability to detect landscape changes. The effects of thematic resolution on many landscape metrics tend to show consistent general patterns, but the details of these patterns are likely to be dependent on specific landscape patterns and classification criteria. Thus, the effects of thematic resolution, like those with regard to grain and extent, must be considered in landscape pattern analysis.


Landscape characterization Image classification Thematic resolution Landscape metrics Landscape pattern analysis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



This research was supported in part by the National Science Foundation under Grant No. BCS-0508002 (Biocomplexity/CNH) and DEB 9714833 (CAP-LTER).


  1. Anderson JR, Hardy E, Roach J, Witmer R (1976) A land use and land cover classification system for use with remote sensor data. US Government Printing Office, WashingtonGoogle Scholar
  2. Baldwin DJB, Weaver K, Schnekenburger F, Perera AH (2004) Sensitivity of landscape pattern indices to input data characteristics on real landscapes: implications for their use in natural disturbance emulation. Landscape Ecol 19:255–271CrossRefGoogle Scholar
  3. Buyantuyev A, Wu J (2006) Characterizing Phoenix urban growth patterns with landscape metrics based on remote sensing data: Effects of thematic resolutions. In: Proceedings of 8th Annual Symposium Central Arizona-Phoenix LTER, Global Institute of Sustainability, Arizona State University, Tempe, pp 11Google Scholar
  4. Federal Geographic Data Committee (1997) Vegetation Classification Standard. Cited 11 Apr 2006
  5. Hargis CD, Bissonette JA, David JL (1998) The behavior of landscape metrics commonly used in the study of habitat fragmentation. Landscape Ecol 13:167–186CrossRefGoogle Scholar
  6. Jelinski DE, Wu J (1996) The modifiable areal unit problem and implications for landscape ecology. Landscape Ecol 11:129–140CrossRefGoogle Scholar
  7. Li H, Reynolds JF (1993) A new contagion index to quantify spatial patterns of landscapes. Landscape Ecol 8:155–162CrossRefGoogle Scholar
  8. Li H, Wu J (2004) Use and misuse of landscape indices. Landscape Ecol 19:389–399CrossRefGoogle Scholar
  9. McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. U.S. Forest Service, Pacific Northwest Research Station, Portland, OregonGoogle Scholar
  10. Neel MC, McGarigal K, Cushman SA (2004) Behavior of class-level landscape metrics across gradients of class aggregation and area. Landscape Ecol 19:435–455CrossRefGoogle Scholar
  11. Openshaw S (1984) The modifiable areal unit problem. Geo Books, Norwich, EnglandGoogle Scholar
  12. Riitters KH, O’Neill RV, Hunsaker CT, Wickham JD, Yankee DH, Timmins KBJ, Jackson BL (1995). A factor analysis of landscape pattern and structure metrics. Landscape Ecol 10:23–39CrossRefGoogle Scholar
  13. Saura S (2004) Effects of remote sensor spatial resolution and data aggregation on selected fragmentation indices. Landscape Ecol 19:197–209CrossRefGoogle Scholar
  14. Scott JM, Jennings MD (1998) Large-area mapping of biodiversity. Ann Mo Bot Gard 85:34–47CrossRefGoogle Scholar
  15. Shen W, Jenerette GD, Wu J, Gardner RH (2004) Evaluating empirical relations of pattern metrics with simulated landscapes. Ecography 27:459–469CrossRefGoogle Scholar
  16. Stefanov WL (2000) 1985, 1990, 1993, 1998 Land cover maps of the Phoenix, Arizona metropolitan area. Geologic Remote Sensing Laboratory, Department of Geological Sciences, Arizona State University, TempeGoogle Scholar
  17. Stefanov WL, Ramsey MS, Christensen PR (2001) Monitoring urban land cover change: an expert system approach to land cover classification of semiarid to arid urban centers. Remote Sens Environ 77:173–185CrossRefGoogle Scholar
  18. Turner MG, O’Neill RV, Gardner RH, Milne BT (1989) Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecol 3:153–162CrossRefGoogle Scholar
  19. Wickham JD, Riitters KH (1995) Sensitivity of landscape metrics to pixel size. Int J Remote Sens 16:3585–3595CrossRefGoogle Scholar
  20. Wu J (2004) Effects of changing scale in landscape pattern analysis: scaling relations. Landscape Ecol 19:125–138CrossRefGoogle Scholar
  21. Wu J (in press) Scale and scaling: a cross-disciplinary perspective. In: Wu J, Hobbs R (eds) Key topics in landscape ecology. Cambridge University Press, Cambridge, UKGoogle Scholar
  22. Wu J, Jelinski DE (1995) Pattern and scale in ecology: the modifiable areal unit problem. In: Li Bo (ed) Lectures in modern ecology. Science Press, Beijing, pp 1–9Google Scholar
  23. Wu J, Jelinski D, Luck M, Tueller P (2000) Multiscale analysis of landscape heterogeneity: scale variance and pattern metrics. Geogr Inform Sci 6:6–19Google Scholar
  24. Wu J, Shen W, Sun W, Tueller P (2002) Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecol 17:761–782CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  1. 1.School of Life Sciences and Global Institute of SustainabilityArizona State UniversityTempeUSA

Personalised recommendations