The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

Students and PhD students of geographical, geological and environmental departments, geophysicists, environmentalists (soil sciences, geography, mining), regulatory agencies, statisticians.

Learning From Geospatial Data: Problems and Important Concepts of Machine Learning – Machine Learning Algorithms for Geospatial Data – Contents of the Book. Software Description – Short Review of the Literature - Exploratory Spatial Data Analysis: Presentation of Data and Case Studies: Exploratory Spatial Data Analysis – Data Pre-Processing – Spatial Correlations: Variography – Presentation of Data – k-Nearest Neighbours Algorithm: a Benchmark Model for Regression and Classification - Geostatistics: Spatial Predictions – Geostatistical Conditional Simulations – Spatial Classification – Software - Machine Learning Algorithms: Artificial Neural Networks: Introduction – Radial Basis Function Neural Networks – General Regression Neural Networks – Probabilistic Neural Networks – Self-Organising Maps – Gaussian Mixture Models And Mixture Density Network • Support Vector Machines And Kernel Methods: Introduction to Statistical Learning Theory – Support Vector Classification – Spatial Data Classification with SVM – Support Vector Regression – Spatial Data Mapping with SVR – Advanced Topics in Kernel Methods.

The Human brain is only 100,000 years old. Yet, this newly evolved organ endows us with unique creative capabilities beyond all other living creatures, including the gift to understand itself. As our very survival and success in life depends on utilizing our brain’s power, intense efforts have begun worldwide to understand the brain, reverse-engineer it and even augment its capacity.

Although solar thermal systems are technologically mature and cost effective, they have not yet been sufficiently used in building design, where they should be playing a greater role in the reduction of fossil-fuel consumption. One main hindrance to adoption is the generally low architectural design quality of the building integration of these thermal systems.

This groundbreaking essay on Le Corbusier provides a new perspective that is based on exhaustive archival research and the study of neglected or completely unknown documents stored at the Fondation Le Corbusier...

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