GIS Tutorial 2
Spatial Analysis Workbook
4th Edition
Published on 3. March 2016
Book
Paperback/Softback
344 pages
978-1-58948-453-5 (ISBN)
Description
GIS Tutorial 2: Spatial Analysis Workbook provides hands-on exercises for intermediate-level GIS users to build problem-solving and analysis skills. A companion to the concepts in The Esri (R) Guide to GIS Analysis book series, GIS Tutorial 2 gives experience with various spatial analysis methods, including location analysis; change over time, location, and value comparisons; geographic distribution; pattern analysis; and cluster identification. This edition has been updated for ArcGIS 10.3 for Desktop. Downloadable data is available on the Esri Press Book Resources web page, esripress.esri.com\bookresources. Additional resources are available for instructors.
Note: This e-book requires ArcGIS software. You can download the ArcGIS Trial at http://www.esri.com/arcgis/trial, contact your school or business Esri Site License Administrator, or purchase a student or individual license through the Esri Store.
Note: This e-book requires ArcGIS software. You can download the ArcGIS Trial at http://www.esri.com/arcgis/trial, contact your school or business Esri Site License Administrator, or purchase a student or individual license through the Esri Store.
More details
Series
Edition
Fourth Edition
Language
English
Place of publication
Redlands
United States
Publishing group
ESRI Press
Target group
College/higher education
Edition type
New edition
Product notice
Paperback (trade)
Illustrations
376 Illustrations
Dimensions
Height: 254 mm
Width: 203 mm
ISBN-13
978-1-58948-453-5 (9781589484535)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Book
01/2013
ESRI Press
€121.08
Article exhausted; check for reprint
Person
David W. Allen is the GIS manager for the City of Euless, Texas. He has taught at Tarrant County College since 1999, where he helped found one of the first GIS degree programs in Texas and establish a state standard for GIS degree programs. He is the author of GIS Tutorial for Python Scripting (Esri Press, 2014), Getting to Know ArcGIS (R) ModelBuilder (TM) (Esri Press, 2011) and the co-author of GIS Tutorial 3: Advanced Workbook (Esri Press, 2010 and Esri Press, forthcoming).
Content
Preface
Acknowledgments
Chapter 1: Mapping where things are
Tutorial 1-1 Working with categories
Tutorial 1-2 Controlling which values are displayed
Tutorial 1-3 Limiting values to display
Chapter 2: Mapping the most and least
Tutorial 2-1 Mapping quantities
Tutorial 2-2 Choosing classes
Tutorial 2-3 Creating a map series
Tutorial 2-4 Working with charts
Chapter 3: Mapping density
Tutorial 3-1 Displaying density for analysis
Tutorial 3-2 Creating dot density maps
Tutorial 3-3 Creating a density surface
Chapter 4: Finding what's inside
Tutorial 4-1 Overlaying datasets for analysis
Tutorial 4-2 Finding features partially inside
Chapter 5: Finding what's nearby
Tutorial 5-1 Selecting features nearby
Tutorial 5-2 Creating buffer features
Tutorial 5-3 Clipping features
Tutorial 5-4 Buffering values
Tutorial 5-5 Using multiple buffer zones
Tutorial 5-6 Quantifying nearness
Tutorial 5-7 Creating distance surfaces
Tutorial 5-8 Calculating cost along a network
Tutorial 5-9 Calculating nearness along a network
Chapter 6: Mapping change
Tutorial 6-1 Mapping change in location
Tutorial 6-2 Mapping change in location and magnitude
Tutorial 6-3 Mapping percentage change in value
Chapter 7: Measuring geographic distribution
Tutorial 7-1 Calculating centers
Tutorial 7-2 Adding weights to centers
Tutorial 7-3 Calculating standard distance
Tutorial 7-4 Calculating a standard deviational ellipse
Tutorial 7-5 Calculating the linear directional mean
Chapter 8: Analyzing patterns
Tutorial 8-1 Using average nearest neighbor
Tutorial 8-2 Identifying the clustering of values
Tutorial 8-3 Checking for multidistance clustering
Tutorial 8-4 Measuring spatial autocorrelation
Chapter 9: Identifying clusters
Tutorial 9-1 Performing cluster and outlier analysis
Tutorial 9-2 Performing hot-spot analysis
Independent projects
Appendix A: Task index
Appendix B: Image and data source credits
Acknowledgments
Chapter 1: Mapping where things are
Tutorial 1-1 Working with categories
Tutorial 1-2 Controlling which values are displayed
Tutorial 1-3 Limiting values to display
Chapter 2: Mapping the most and least
Tutorial 2-1 Mapping quantities
Tutorial 2-2 Choosing classes
Tutorial 2-3 Creating a map series
Tutorial 2-4 Working with charts
Chapter 3: Mapping density
Tutorial 3-1 Displaying density for analysis
Tutorial 3-2 Creating dot density maps
Tutorial 3-3 Creating a density surface
Chapter 4: Finding what's inside
Tutorial 4-1 Overlaying datasets for analysis
Tutorial 4-2 Finding features partially inside
Chapter 5: Finding what's nearby
Tutorial 5-1 Selecting features nearby
Tutorial 5-2 Creating buffer features
Tutorial 5-3 Clipping features
Tutorial 5-4 Buffering values
Tutorial 5-5 Using multiple buffer zones
Tutorial 5-6 Quantifying nearness
Tutorial 5-7 Creating distance surfaces
Tutorial 5-8 Calculating cost along a network
Tutorial 5-9 Calculating nearness along a network
Chapter 6: Mapping change
Tutorial 6-1 Mapping change in location
Tutorial 6-2 Mapping change in location and magnitude
Tutorial 6-3 Mapping percentage change in value
Chapter 7: Measuring geographic distribution
Tutorial 7-1 Calculating centers
Tutorial 7-2 Adding weights to centers
Tutorial 7-3 Calculating standard distance
Tutorial 7-4 Calculating a standard deviational ellipse
Tutorial 7-5 Calculating the linear directional mean
Chapter 8: Analyzing patterns
Tutorial 8-1 Using average nearest neighbor
Tutorial 8-2 Identifying the clustering of values
Tutorial 8-3 Checking for multidistance clustering
Tutorial 8-4 Measuring spatial autocorrelation
Chapter 9: Identifying clusters
Tutorial 9-1 Performing cluster and outlier analysis
Tutorial 9-2 Performing hot-spot analysis
Independent projects
Appendix A: Task index
Appendix B: Image and data source credits