Spatial analysis : statistics, visualization, and computational methods / Tonny J. Oyana and Florence M. Margai.
Material type:
TextPublication details: Boca Raton : CRC Press, ©2016.Description: xviii, 305 pages : illustrations (some color) ; 24 cmISBN: - 9781498707633
- 000SB:910 23 Oy98
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SB:910 Oy98 (Browse shelf(Opens below)) | Available | 137469 |
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| 000SB:910 M439 Quantative and statistical approaches to geography | 000SB:910 M726 Spatial statistics and computational methods | 000SB:910 N827 Interntial statistics for geographers | 000SB:910 Oy98 Spatial analysis : | 000SB:910 P153 Statistical techniques | 000SB:910 R355 Applications of statistical sampling to geographical studies with special reference to cartographic representation of sampling error | 000SB:910 T245 Quantitative methods in geography |
Includes bibliographical references and index.
1. Understanding the context and relevance of spatial analysis --
2. Making scientific observations and measurements in spatial analysis --
3. Using statistical measures to analyze data distributions --
4. Engaging in exploratory data analysis, visualization, and hypothesis testing --
5.Understanding spatial statistical relationships --
6. Engaging in point pattern analysis --
7. Engaging in areal pattern analysis using global and local statistics --
8. Engaging in geostatistical analysis --
9. Data science : understanding computing systems and analytics for big data.
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis--containing hands-on problem-set that can be worked out in MS Excel or ArcGIS--as well as detailed illustrations and numerous case studies.
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