Characterizing Categorical Map Patterns Using Neutral Landscape Models

  • Gardner R
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Abstract

This title meets a great demand for training in spatial analysis tools accessible to a wide audience. Landscape ecology continues to grow as an exciting discipline with much to offer for solving pressing and emerging problems in environmental science. Much of the strength of landscape ecology lies in its ability to address challenges over large areas, over spatial and temporal scales at which decision-making often occurs. As the world tackles issues related to sustainability and global change, the need for this broad perspective has only increased. Furthermore, spatial data and spatial analysis (core methods in landscape ecology) are critical for analyzing land-cover changes world-wide. While spatial dynamics have long been fundamental to terrestrial conservation strategies, land management and reserve design, mapping and spatial themes are increasingly recognized as important for ecosystem management in aquatic, coastal and marine systems. This second edition is purposefully more applied and international in its examples, approaches, perspectives and contributors. It includes new advances in quantifying landscape structure and connectivity (such as graph theory), as well as labs that incorporate the latest scientific understanding of ecosystem services, resilience, social-ecological landscapes, and even seascapes. Of course, as before, the exercises emphasize easy-to-use, widely available software.

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APA

Gardner, R. H. (2017). Characterizing Categorical Map Patterns Using Neutral Landscape Models. In Learning Landscape Ecology (pp. 83–103). Springer New York. https://doi.org/10.1007/978-1-4939-6374-4_6

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