Spatial Entropy And Landscape Analysis
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Spatial Entropy and Landscape Analysis
Author: Fivos Papadimitriou
language: en
Publisher: Springer Nature
Release Date: 2022-02-03
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.
Modelling Landscape Dynamics
Author: Fivos Papadimitriou
language: en
Publisher: Springer Nature
Release Date: 2024-01-02
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.
Spatial Artificial Intelligence
Author: Fivos Papadimitriou
language: en
Publisher: Springer Nature
Release Date: 2025-02-08
This is the first book that focuses on the full range of spatial aspects of Artificial Intelligence. Spatial AI is defined here as - AI that is generated from spatial data, or - AI that is used for spatial analysis and spatial problem-solving, or - AI that is embedded in spatial (physical and/or digital) domains. The reader is presented with a comprehensive exploration of the rise of Spatial AI in the last decades, its applications in spatial analysis and its relationships with GeoAI, Evolutionary AI and Spatial Computing. With chapters addressing the spatial aspects of AI in the context of GenAI, AR, robotics, digital twins etc, it is a valuable resource for those who seek to explore the immense potential of Spatial AI, its possible limitations in terms of energy and computability, as well as its future prospects towards spatially-enabled AGI and Artificial Super-Intelligence.