Spatial context. An introduction to fundamental computer algorithms for spatial analysis (Q2797097)

Spatial analysis is about analyzing spatial data that describe geometric relations between physical objects in space. Applications are in areas as diverse as astronomy, VLSI design, and geographic information systems. Challenges are in acquiring the data needed, in building suitable models, and in processing the data efficiently. Good solutions are typically based on theoretical insight into structural geometric properties that lead to efficient algorithms; such results are mostly from computational geometry, a theoretical branch of computer science. In addition, sound design and implementation techniques are required that enable large-scale applications.NEWLINENEWLINEThe author of the present book is a well-known expert in this field. His book starts with a presentation of useful geometric primitives like predicates for 3-dimensional intersection detection. The next, and central, topic are geometric structures of immense value to modeling. Most prominently feature the Voronoi diagram, the Delaunay triangulation and the medial axis (or: skeleton). They contain a lot of information about a given scene and are, therefore, widely used in computer science, GIS, mathematics, natural sciences, economics, and ecology. The author discusses surprising properties of these structures, emphasizing general concepts like duality. The third part of the book is devoted to more practically oriented methods used in 2- and 3-dimensional GIS.NEWLINENEWLINEIn this book, the author presents a rather personal view. His selection of topics, the decision not to include complexity questions or numerical problems, and the wealth of beautiful figures make reading easy. The author's enthusiasm jumps out at his readers and keeps them motivated. This book provides, in a pleasurable way, insight into topics that are not widely known nor easily accessible. Thus, it presents a very nice introduction to spatial analysis.