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Spatial analysis : statistics, visualization, and computational methods / Tonny J. Oyana and Florence M. Margai.

By: Contributor(s): Material type: TextTextPublication details: Boca Raton : CRC Press, ©2016.Description: xviii, 305 pages : illustrations (some color) ; 24 cmISBN:
  • 9781498707633
Subject(s): DDC classification:
  • 000SB:910 23 Oy98
Contents:
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.
Summary: 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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Holdings
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
Total holds: 0

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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