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Algorithmic Foundation of Multi-Scale Spatial Representation (Paperback)
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Algorithmic Foundation of Multi-Scale Spatial Representation (Paperback)
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With the widespread use of GIS, multi-scale representation has
become an important issue in the realm of spatial data handling.
However, no book to date has systematically tackled the different
aspects of this discipline. Emphasizing map generalization,
Algorithmic Foundation of Multi-Scale Spatial Representation
addresses the mathematical basis of multi-scale representation,
specifically, the algorithmic foundation. Using easy-to-understand
language, the author focuses on geometric transformations, with
each chapter surveying a particular spatial feature. After an
introduction to the essential operations required for geometric
transformations as well as some mathematical and theoretical
background, the book describes algorithms for a class of point
features/clusters. It then examines algorithms for individual line
features, such as the reduction of data points, smoothing
(filtering), and scale-driven generalization, followed by a
discussion of algorithms for a class of line features including
contours, hydrographic (river) networks, and transportation
networks. The author also addresses algorithms for individual area
features, a class of area features, and various displacement
operations. The final chapter briefly covers algorithms for 3-D
surfaces and 3-D features. Providing a thorough treatment of
low-level algorithms, Algorithmic Foundation of Multi-Scale Spatial
Representation supplies the mathematical groundwork for multi-scale
representations of spatial data.
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