Environmental and Ecological Statistics

, Volume 8, Issue 1, pp 5–20

Fragmentation profiles for real and simulated landscapes

  • Glen D. Johnson
  • Wayne L. Myers
  • Ganapati P. Patil
  • Charles Taillie
Article

DOI: 10.1023/A:1009651914734

Cite this article as:
Johnson, G.D., Myers, W.L., Patil, G.P. et al. Environmental and Ecological Statistics (2001) 8: 5. doi:10.1023/A:1009651914734

Abstract

When a natural landscape is represented by a series of categorical raster maps of varying resolution, a multiresolution characterization of spatial pattern can be obtained in which entropy is computed at each resolution conditional on the next coarser resolution. The series of entropy values is plotted as a function of resolution, resulting in a multiresolution profile of fragmentation pattern in the landscape. If a categorical raster map is available at a single resolution only, a series of degraded maps at increasingly coarser resolutions is generated and the fragmentation profile is computed for this series. An algorithm has been developed for obtaining the profile directly from the single resolution map without having to generate and store the coarser resolution maps. A hierarchical stochastic model is described for simulating categorical raster maps and the fragmentation profile of the generating process is obtained in terms of the model parameters. These “process” profiles provide benchmarks for assessing empirical profiles obtained from raster maps of actual landscapes. Methods of the paper are applied to several watersheds of Pennsylvania using landcover maps derived from satellite imagery. These examples indicate that characteristic landscape types induce characteristic features in their fragmentation profiles.

categorical raster maps conditional entropy diagonal dominance HMTM model landscape ecology Markov transition matrix multiresolution spatial pattern self-similarity 

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Glen D. Johnson
    • 1
  • Wayne L. Myers
    • 2
  • Ganapati P. Patil
    • 1
  • Charles Taillie
    • 1
  1. 1.Department of StatisticsCenter for Statistical Ecology and Environmental StatisticsUSA
  2. 2.School of Forest Resources and Environmental Resources Research InstitutePenn State UniversityUniversity ParkUSA

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