Spatial Data Analysis For Geographic Information Science
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Multicriteria Decision Analysis in Geographic Information Science
This book is intended for the GIS Science and Decision Science communities. It is primarily targeted at postgraduate students and practitioners in GIS and urban, regional and environmental planning as well as applied decision analysis. It is also suitable for those studying and working with spatial decision support systems. The main objectives of this book are to effectivley integrate Multicriteria Decision Analysis (MCDA) into Geographic Information Science (GIScience), to provide a comprehensive account of theories, methods, technologies and tools for tackling spatial decision problems and to demonstrate how the GIS-MCDA approaches can be used in a wide range of planning and management situations.
Geographical Data Science and Spatial Data Analysis
We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
Spatial Analytical Perspectives on GIS
The ability to manipulate spatial data in different forms and to extract additional meaning from them is at the heart of GIS, yet genuine spatial analysis tools are rarely incorporated into commercial software, thus seriously limiting their usefulness. The future of GIS technology wil depend largely on the incorporation of more powerful analytical and modelling functions - and there is agreement within the GIS community of the urgent need to address these issues. This text attempts this task. It presents the latest information on incorporating spatial analysis tools into GIS, and includes concepts and applications from both the environmental and socio-econimc sciences.