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This book offers a comprehensive exposition of the mathematical methods that can be used to model landscape dynamics. It is systematically shown how mathematical models of progressively higher complexity can be derived from ordinary landscape maps and related data in ways that enable researchers to predict future landscape transformations and to assess landscape stability, sustainability and resilience.These models are deterministic (i.e. linear or non-linear systems of differential equations), stochastic (i.e. Markovian), or combined deterministic-and-stochastic (using stochastic differential equations), whereas topics and challenging problems related to complexity (spatial randomness, chaotic behaviors, riddled systems etc) are also examined in the book.
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This book offers a comprehensive exposition of the mathematical methods that can be used to model landscape dynamics. It is systematically shown how mathematical models of progressively higher complexity can be derived from ordinary landscape maps and related data in ways that enable researchers to predict future landscape transformations and to assess landscape stability, sustainability and resilience.These models are deterministic (i.e. linear or non-linear systems of differential equations), stochastic (i.e. Markovian), or combined deterministic-and-stochastic (using stochastic differential equations), whereas topics and challenging problems related to complexity (spatial randomness, chaotic behaviors, riddled systems etc) are also examined in the book.
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