By: Jay Lee and David Wong
192 pages, Figs, tabs, maps
The first book to bring the traditional tools of quantitative geography into the GIS environment.
...a very practical introductory book. (URISA Journal, Fall 2001/ Spring 2002)
1. Attribute Descriptors; 1.1 Central Tendency; 1.2 Dispersion and Distribution; 1.3 Relationship; 1.4 Trend; 2. Point Descriptors; 2.1 The Nature of Point Features; 2.2 Central Tendency of Point Distributions; 2.3 Dispersion of Point Distributions; 2.4 Application Examples; 2.4.1 References; 3. Pattern Detectors; 3.1 Scale, Extent, and Projection; 3.2 Quadrat Analysis; 3.3 Nearest Neighbor Analysis; 3.4 Spatial Autocorrelation; 3.5 Application Examples; 3.5.1 References; 4. Line Descriptors; 4.1 The Nature of Linear Features; 4.2 Characteristics and Attributes of Linear Features; 4.3 Directional Statistics; 4.4 Network Analysis; 4.5 Application Examples; 4.5.1 References; 5. Pattern Descriptors; 5.1 Spatial Relationships; 5.2 Spatial Autocorrelation; 5.3 Spatial Weights Matrices; 5.4 Types of Spatial Autocorrelation Measures and Some Notations; 5.5 Joint Count Statistics; 5.6 Moran and Geary Indices; 5.7 General G-Statistic; 5.8 Local Spatial Autocorrelation Statistics; 5.9 Moran Scatterplot; 5.10 Application Examples; 5.11 Summary; 5.11.1 References; Index
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Jay Lee, PhD, is Associate Professor of Geography at Kent State University in Ohio and served as associate editor of the Wiley journal, Applied Geographic Studies. David W.S. Wong, PhD, is Associate Professor of Earth Sciences at George Mason University in Fairfax, Virginia.
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