This book delivers stimulating input for a broad range of researchers, from geographers and ecologists to psychologists interested in spatial perception and physicists researching in complex systems. How can one decide whether one surface or spatial object is more complex than another? What does it require to measure the spatial complexity of small maps, and why does this matter for nature, science and technology? Drawing from algorithmics, geometry, topology, probability and informatics, and with examples from everyday life, the reader is invited to cross the borders into the bewildering realm of spatial complexity, as it emerges from the study of geographic maps, landscapes, surfaces, knots, 3D and 4D objects. The mathematical and cartographic experiments described in this book lead to hypotheses and enigmas with ramifications in aesthetics and epistemology.

This book delivers stimulating input for a broad range of researchers, from geographers and ecologists to psychologists interested in spatial perception and physicists researching in complex systems. How can one decide whether one surface or spatial object is more complex than another? What does it require to measure the spatial complexity of small maps, and why does this matter for nature, science and technology? Drawing from algorithmics, geometry, topology, probability and informatics, and with examples from everyday life, the reader is invited to cross the borders into the bewildering realm of spatial complexity, as it emerges from the study of geographic maps, landscapes, surfaces, knots, 3D and 4D objects. The mathematical and cartographic experiments described in this book lead to hypotheses and enigmas with ramifications in aesthetics and epistemology.

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.

This is the first book on spatial entropy in the scientific literature. It links spatial entropy with landscape analysis, landscape diversity and geo-information. It gives all the essential tools that a researcher needs in order to study the spatial entropy of physical as well as artificial landscapes (created with artificial life, swarm intelligence etc). This book explores the fascinating world of the interplay between spatial entropy, spatial information, self-organization and emergence and gives geographers and landscape scientists several alternative mathematical methods to study them, i.e. Shannon's formula, measures from non-extensive thermodynamics, from directional statistics and network theory. An essential book for researchers in landscape analysis and geo-informatics.