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Uncovering Dominant Land-Cover Patterns of Quebec: Representative Landscapes, Spatial Clusters, and Fences

Author

Listed:
  • Kevin Partington

    (Département des Sciences du Bois et de la Forêt, Université Laval, 2405 rue de la Terrasse, Québec, QC G1V0A6, Canada)

  • Jeffrey A. Cardille

    (Department of Natural Resource Sciences, McGill University, 21111 Lakeshore, Ste-Anne-de-Bellevue, QC H9X3V9, Canada)

Abstract

Mapping large areas for planning and conservation is a challenge undergoing rapid transformation. For centuries, the creation of broad-extent maps was the near-exclusive domain of expert specialist cartographers, who painstakingly delineated regions of relative homogeneity with respect to a given set of criteria. In the satellite era, it has become possible to rapidly create and update categorizations of Earth’s surface with improved speed and flexibility. Land cover datasets and landscape metrics offer a vast set of information for viewing and quantifying land cover across large areas. Comprehending the patterns revealed by hundreds of possibly relevant landscape metric values, however, remains a daunting task. We studied the information content of a large set of landscape pattern metrics across Quebec, Canada, asking whether they were capable of making consistent, spatially cohesive distinctions among patterns in landscapes. We evaluated the possibility of metrics to identify representative landscapes for efficient sampling or conservation, and determined areas where differences in nearby landscape patterns were the most and least pronounced. This approach can serve as a template for a landscape perspective on the challenges that will be faced in the near future by planners and conservationists working across large areas.

Suggested Citation

  • Kevin Partington & Jeffrey A. Cardille, 2013. "Uncovering Dominant Land-Cover Patterns of Quebec: Representative Landscapes, Spatial Clusters, and Fences," Land, MDPI, vol. 2(4), pages 1-18, December.
  • Handle: RePEc:gam:jlands:v:2:y:2013:i:4:p:756-773:d:31125
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    Cited by:

    1. Nowosad, Jakub & Stepinski, Tomasz, 2018. "Spatial association between regionalizations using the information-theoretical V-measure," Earth Arxiv rcjh7, Center for Open Science.

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