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.

This book shows how to successfully adapt entropy measures to the complexity of environmental data. It also provides a unified framework that covers all main entropy and spatial entropy measures in the literature, with suggestions for their potential use in the analysis of environmental data such as biodiversity, land use and other phenomena occurring over space or time, or both. First, recent literature reviews about including spatial information in traditional entropy measures are presented, highlighting the advantages and disadvantages of past approaches and the difference in interpretation of their proposals. A consistent notation applicable to all approaches is introduced, and the authors’ own proposal is presented. Second, the use of entropy in spatial sampling is focused on, and a method with an outstanding performance when data show a negative or complex spatial correlation is proposed. The last part of the book covers estimating entropy and proposes a model-based approach that differs from all existing estimators, working with data presenting any departure from independence: presence of covariates, temporal or spatial correlation, or both. The theoretical parts are supported by environmental examples covering point data about biodiversity and lattice data about land use. Moreover, a practical section is provided for all parts of the book; in particular, the R package SpatEntropy covers not only the authors’ novel proposals, but also all the main entropy and spatial entropy indices available in the literature. R codes are supplemented to reproduce all the examples. This book is a valuable resource for students and researchers in applied sciences where the use of entropy measures is of interest and where data present dependence on space, time or covariates, such as geography, ecology, biology and landscape analysis.

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.

Geo-Topology is an exploration of the depth and breadth of the relationships between Geography and Topology, with applications ranging from Landscape Geography to Social Geography and from Spatial Analysis to Geospatial Technologies. It shows how topics of geographical research (landscapes, borders, spatial social relationships etc) can be examined by using mathematical concepts and methods of Topology, exposing the realm of geo-topological modelling and visualization through Point-Set Topology, Knot Theory, Reeb graphs, Topological Surfaces (i.e. Möbius bands and Klein bottles), Differential Topology, Network Analysis, Combinatorial Topology, Braid Theory and Ultrametric Topology. Besides geographers, this book is a trove of new ideas for landscape ecologists, mathematicians, data scientists, sociologists, psychologists, anthropologists and educators. Geo-Topology is a systematic introduction to topological thinking in Geography, also by highlighting the significance of Topology for Geographical Education, as well as for the Philosophy and Epistemology of Geography.

Geo-Topology is an exploration of the depth and breadth of the relationships between Geography and Topology, with applications ranging from Landscape Geography to Social Geography and from Spatial Analysis to Geospatial Technologies. It shows how topics of geographical research (landscapes, borders, spatial social relationships etc) can be examined by using mathematical concepts and methods of Topology, exposing the realm of geo-topological modelling and visualization through Point-Set Topology, Knot Theory, Reeb graphs, Topological Surfaces (i.e. Möbius bands and Klein bottles), Differential Topology, Network Analysis, Combinatorial Topology, Braid Theory and Ultrametric Topology. Besides geographers, this book is a trove of new ideas for landscape ecologists, mathematicians, data scientists, sociologists, psychologists, anthropologists and educators. Geo-Topology is a systematic introduction to topological thinking in Geography, also by highlighting the significance of Topology for Geographical Education, as well as for the Philosophy and Epistemology of Geography.

This book presents a new method for assessing spatial pattern in raster land cover maps based on satellite imagery in a way that incorporates multiple pixel resolutions. This is combined with more conventional single-resolution measurements of spatial pattern and simple non-spatial land cover proportions to assess predictability of both surface water quality and ecological integrity within watersheds of the state of Pennsylvania (USA).