Skip to main content
Book cover

Learning Landscape Ecology pp 45–63Cite as

Understanding Landscape Metrics

Abstract

An extensive set of landscape metrics exists to quantify spatial patterns in heterogeneous landscapes. Developers and users of these metrics typically seek to objectively describe landscapes that humans assess subjectively as, for example, “clumpy,” “dispersed,” “random,” “diverse,” “fragmented,” or “connected.” Because the quantification of pattern is fundamental to many of the relationships we seek to understand in landscape ecology, a basic familiarity with the most commonly used metrics is extremely important. Several software programs evaluate maps quickly and cheaply, but there are no absolute rules governing the proper use of landscape metrics. To help foster the appropriate use of landscape metrics, in this lab students will.

Keywords

  • Cover Type
  • Landscape Pattern
  • Landscape Metrics
  • Edge Density
  • Landscape Composition

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4939-6374-4_4
  • Chapter length: 19 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-1-4939-6374-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   99.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Figure 4.1
Figure 4.2

References and Recommended Readings

NOTE: An asterisk preceding the entry indicates that it is a suggested reading.

  • Baker WL, Cai Y (1992) The r.le programs for multi-scale analysis of landscape structure using the GRASS geographical information system. Landsc Ecol 7:291–302

    CrossRef  Google Scholar 

  • Boström C, Pittman SJ, Simenstad C, Kneib RT (2011) Seascape ecology of coastal biogenic habitats: advances, gaps, and challenges. Mar Ecol Prog Ser 427:191–217

    CrossRef  Google Scholar 

  • *Burnicki AC (2012) Impact of error on landscape pattern analyses performed on land-cover change maps. Landsc Ecol 27:713–729. Accuracy of the data used in any landscape analysis will influence the results, and this is especially important when you want to use metrics to quantify how landscapes change over time.

    Google Scholar 

  • Cardille JA, Lambois M (2010) From the redwood forest to the Gulf Stream waters: human signature nearly ubiquitous in representative US landscapes. Front Ecol Environ 8:130–134

    CrossRef  Google Scholar 

  • Corry RC, Nassauer JI (2005) Limitations of using landscape pattern indices to evaluate the ecological consequences of alternative plans and designs. Landsc Urban Plann 72:265–280

    CrossRef  Google Scholar 

  • *Cushman SA, McGarigal K, Neel MC (2008) Parsimony in landscape metrics: strength, universality and consistency. Ecol Indicators 8:691–703. Many landscape metrics are correlated with one another, and this paper emphasizes the unique contributions of metrics that are independent of one another and associated with qualitatively different aspects of pattern.

    Google Scholar 

  • Fortin M-J, Boots B, Csillag F, Remmel TK (2003) On the role of spatial stochastic models in understanding landscape indices. Oikos 102:203–212

    CrossRef  Google Scholar 

  • Gardner RH, Milne BT, Turner MG et al (1987) Neutral models for the analysis of broad-scale landscape pattern. Landsc Ecol 1:19–28

    CrossRef  Google Scholar 

  • *Gustafson EJ (1998) Quantifying landscape spatial pattern: what is the state of the art? Ecosystems 1:143–156. A synthetic overview of the ways in which landscape pattern is quantified, this classic paper emphasizes conceptual issues and distinguishes between metrics, including patch-based metrics, calculated from categorical data and approaches from spatial statistics.

    Google Scholar 

  • Gustafson EJ, Parker GR (1992) Relationships between landcover proportion and indices of landscape spatial pattern. Landsc Ecol 7:101–110

    CrossRef  Google Scholar 

  • *Haines-Young R, Chopping M (1996) Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Progr Phys Geogr 20:418–445. A good review that includes examples of how different landscape metrics are used in questions associated with forested landscapes.

    Google Scholar 

  • Homer C, Huang C, Yang L et al (2004) Development of a 2001 National Land-Cover Database for the United States. Photogramm Eng Remote Sens 70(7):829–840

    CrossRef  Google Scholar 

  • Jin S, Yang L, Danielson P et al (2013) A comprehensive change detection method for updating the national land cover database to circa 2011. Remote Sens Environ 132:159–175

    CrossRef  Google Scholar 

  • *Li H, Reynolds JF (1995) On definition and quantification of heterogeneity. Oikos 73:280–284. An excellent discussion of what is meant by heterogeneity. This seminal paper emphasizes understanding what is being quantified and should be read by all those beginning to consider the causes or consequences of spatial pattern.

    Google Scholar 

  • Li H, Reynolds JF (1993) A new contagion index to quantify spatial patterns of landscapes. Landsc Ecol 8:155–162

    CrossRef  Google Scholar 

  • Li H, Reynolds JF (1994) A simulation experiment to quantify spatial heterogeneity in categorical maps. Ecology 75:2446–2455

    CrossRef  Google Scholar 

  • *Li H, Wu J (2004) Use and misuse of landscape indices. Landsc Ecol 19:389–399. Useful synthesis of issues associated with quantifying landscape patterns.

    Google Scholar 

  • McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html

  • McGarigal K, Marks BJ (1993) FRAGSTATS. Spatial analysis program for quantifying landscape structure. USDA Forest Service General Technical Report PNW-GTR-351

    Google Scholar 

  • O’Neill RV, Krummel JR, Gardner RH et al (1988) Indices of landscape pattern. Landsc Ecol 1:153–162

    CrossRef  Google Scholar 

  • Pielou EC (1975) Ecological diversity. Wiley-Interscience, New York

    Google Scholar 

  • Remmel TK, Csillag F (2003) When are two landscape pattern indices significantly different? J Geograph Syst 5:331–351

    CrossRef  Google Scholar 

  • Riitters KH, O’Neill RV, Wickham JD et al (1996) A note on contagion indices for landscape analysis. Landsc Ecol 11:197–202

    CrossRef  Google Scholar 

  • Romme WH (1982) Fire and landscape diversity in subalpine forests of Yellowstone National Park. Ecol Monogr 52:199–221

    CrossRef  Google Scholar 

  • Romme WH, Knight DH (1982) Landscape diversity: the concept applied to Yellowstone Park. BioScience 32:664–670

    CrossRef  Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423. (July), with corrections pp. 623–656 (October)

    Google Scholar 

  • *Símovsá P, Gdulová K (2012) Landscape indices behavior: A review of scale effects. Appl Geogr 34:385–394. There are a fair number of empirical papers documenting the consequences of changing grain and extent on landscape metrics, and this paper provides an overview.

    Google Scholar 

  • Teixido N, Garrabou J, Gutt J et al (2007) Iceberg disturbance and successional spatial patterns: the case of the shelf Antarctic benthic communities. Ecosystems 10:142–157

    CrossRef  Google Scholar 

  • Turner MG (2005) Landscape ecology: what is the state of the science? Ann Rev Ecol Evol Syst 36:319–344

    CrossRef  Google Scholar 

  • *Turner MG, Gardner RH (2015) Chapter 4, Landscape metrics. In: Landscape ecology in theory and practice. Springer, New York, pp 97–142. We highly recommend reading this chapter from the landscape ecology text, as it provides an introduction and overview of why and how to use landscape metrics in spatial pattern analysis.

    Google Scholar 

  • Turner MG, Costanza R, Sklar FH (1989) Methods to compare spatial patterns for landscape modeling and analysis. Ecol Model 48:1–18

    CrossRef  Google Scholar 

  • Vogelmann JE, Howard SM, Yang L et al (2001) Completion of the 1990s National Land Cover Data Set for the conterminous United States from Landsat Thematic Mapper data and ancillary data sources. Photogramm Eng Remote Sens 67(6):650–662

    Google Scholar 

  • Wickham JD, Norton DJ (1994) Mapping and analyzing landscape patterns. Landsc Ecol 9:7–23

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. McGill University, Sainte Anne de Bellevue, QC, Canada

    Jeffrey A. Cardille

  2. University of Wisconsin-Madison, Madison, WI, USA

    Monica G. Turner

Authors
  1. Jeffrey A. Cardille
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Monica G. Turner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeffrey A. Cardille .

Editor information

Editors and Affiliations

  1. University of British Columbia, Department of Forest and Conservation Sciences, Vancouver, British Columbia, Canada

    Sarah E. Gergel

  2. University of Wisconsin-Madison, Department of Zoology, Madison, Wisconsin, USA

    Monica G. Turner

Rights and permissions

Reprints and Permissions

Copyright information

© 2017 Springer-Verlag New York

About this chapter

Cite this chapter

Cardille, J.A., Turner, M.G. (2017). Understanding Landscape Metrics. In: Gergel, S., Turner, M. (eds) Learning Landscape Ecology. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6374-4_4

Download citation