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R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons. The R-tree was proposed by Antonin Guttman in 1984 [2] and has found significant use in both theoretical and applied contexts. [3]
Chapter 3 concerns data structures for geographic information systems, data formatting based on raster graphics and vector graphics, methods for buffer analysis, [3] and its uses in turning point and line data into area data. Later in the book, but fitting thematically into this part, [1] [4] chapter 9 covers map projections. [3]
In data processing R*-trees are a variant of R-trees used for indexing spatial information. R*-trees have slightly higher construction cost than standard R-trees, as the data may need to be reinserted; but the resulting tree will usually have a better query performance. Like the standard R-tree, it can store both point and spatial data.
Compression algorithms identify spatial patterns in the data, then transform the data into parameterized representations of the patterns, from which the original data can be reconstructed. In most GIS applications, lossless compression algorithms (e.g., Lempel-Ziv ) are preferred over lossy ones (e.g., JPEG ), because the complete original data ...
The data associated with a leaf cell varies by application, but the leaf cell represents a "unit of interesting spatial information". The subdivided regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. [1] A similar partitioning is also known as ...
The handbook contains survey chapters in classical and new studies in geometric algorithms: hyperplane arrangements, Voronoi diagrams, geometric and spatial data structures, polygon decomposition, randomized algorithms, derandomization, parallel computational geometry (deterministic and randomized), visibility, Art Gallery and Illumination ...
On the other hand, data driven structures such as R-trees can be more efficient for data storage and speed at search execution time, though they are generally tied to the internal structure of a given data storage system. The use of such spatial indices is not limited to digital data; the "index" section of any global or street atlas commonly ...
Download as PDF; Printable version; In other projects ... Pages in category "Geographic information systems" ... List of GIS data sources; List of spatial analysis ...