Making Spatial Decisions Using GIS and Remote Sensing
A Workbook
Published on 25. November 2013
Book
Paperback/Softback
300 pages
978-1-58948-336-1 (ISBN)
Description
Making Spatial Decisions Using GIS and Remote Sensing is the first workbook to highlight the image processing capabilities inherent in ArcGIS software. Designed to complement remote sensing textbooks in an undergraduate curriculum, this workbook teaches students image processing and analysis skills with ArcGIS 10.1 for Desktop. The book uses step-by-step instruction, guided activities that reinforce learned concepts, and independent projects that encourage students to solve problems using local data.
A DVD with Landsat imagery and other data accompanies the book along with access to ArcGIS 10.1 for Desktop Advanced software (180-day use). Instructor resources are available.
A DVD with Landsat imagery and other data accompanies the book along with access to ArcGIS 10.1 for Desktop Advanced software (180-day use). Instructor resources are available.
More details
Language
English
Place of publication
Redlands
United States
Illustrations
117 illustrations
ISBN-13
978-1-58948-336-1 (9781589483361)
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
Persons
Kathryn Keranen is an instructor at James Madison University and the co-founder of the dual enrollment Geospatial Semester. She is a curriculum writer and co-author of Making Spatial Decisions Using GIS (Esri Press 2011).
Robert Kolvoord is a professor at James Madison University where he also serves as the interim dean of the College of Integrated Science and Engineering. He is a researcher, curriculum developer, and co-author of Making Spatial Decisions Using GIS (Esri Press 2011).
Robert Kolvoord is a professor at James Madison University where he also serves as the interim dean of the College of Integrated Science and Engineering. He is a researcher, curriculum developer, and co-author of Making Spatial Decisions Using GIS (Esri Press 2011).
Content
Preface
Acknowledgments
Introduction
Workflow
Module 1 - Enhancing images
Project 1: Displaying and enhancing Landsat imagery of the Chesapeake Bay
Project 2: Displaying and enhancing Landsat imagery of Las Vegas, Nevada
Project 3: On your own
Module 2 - Composite images
Project 1: Creating multispectral imagery of the Chesapeake Bay
Project 2: Creating multispectral imagery of Las Vegas, Nevada
Project 3: On your own
Module 3 - Spectral signatures
Project 1: Investigating spectral signatures of the Chesapeake Bay
Project 2: Investigating spectral signatures of Las Vegas, Nevada
Project 3: On your own
Module 4 - Land cover
Project 1: Comparing digitized land cover to USGS land-cover classes in Loudoun County, Virginia
Project 2: Comparing digitized land cover to USGS land-cover classes near Lake Mohave
Project 3: On your own
Module 5 - Unsupervised classification
Project 1: Calculating unsupervised classification of the Chesapeake Bay
Project 2: Calculating unsupervised classification of Las Vegas, Nevada
Project 3: On your own
Module 6 - Supervised classification
Project 1: Calculating supervised classification of the Chesapeake Bay
Project 2: Calculating supervised classification of Las Vegas, Nevada
Project 3: On your own
Module 7 - Classification accuracy
Project 1: Assessing the accuracy of land-cover data and different types of classification of the Chesapeake Bay
Project 2: Assessing the accuracy of land-cover data and different types of classifications of Las Vegas, Nevada
Project 3: On your own
Module 8 - Urban change
Project 1: Measuring urban change in Loudoun County, Virginia
Project 2: Measuring urban change in Las Vegas, Nevada
Project 3: On your own
Module 9 - Water
Project 1: Measuring the impact of drought on Texas reservoirs
Project 2: Measuring Minnesota lake temperature using thermal infrared data
Project 3: On your own
Module 10 - Normalized Difference Vegetation Index
Project 1: Using NDVI to study drought conditions in Texas
Project 2: Using NDVI to study seasonal change in Minnesota
Project 3: On your own
Appendix A: Downloading Landsat imagery
Appendix B: References
Appendix C: Image and data credits
Appendix D: Data license agreement
Appendix E: Installing the data and software
Acknowledgments
Introduction
Workflow
Module 1 - Enhancing images
Project 1: Displaying and enhancing Landsat imagery of the Chesapeake Bay
Project 2: Displaying and enhancing Landsat imagery of Las Vegas, Nevada
Project 3: On your own
Module 2 - Composite images
Project 1: Creating multispectral imagery of the Chesapeake Bay
Project 2: Creating multispectral imagery of Las Vegas, Nevada
Project 3: On your own
Module 3 - Spectral signatures
Project 1: Investigating spectral signatures of the Chesapeake Bay
Project 2: Investigating spectral signatures of Las Vegas, Nevada
Project 3: On your own
Module 4 - Land cover
Project 1: Comparing digitized land cover to USGS land-cover classes in Loudoun County, Virginia
Project 2: Comparing digitized land cover to USGS land-cover classes near Lake Mohave
Project 3: On your own
Module 5 - Unsupervised classification
Project 1: Calculating unsupervised classification of the Chesapeake Bay
Project 2: Calculating unsupervised classification of Las Vegas, Nevada
Project 3: On your own
Module 6 - Supervised classification
Project 1: Calculating supervised classification of the Chesapeake Bay
Project 2: Calculating supervised classification of Las Vegas, Nevada
Project 3: On your own
Module 7 - Classification accuracy
Project 1: Assessing the accuracy of land-cover data and different types of classification of the Chesapeake Bay
Project 2: Assessing the accuracy of land-cover data and different types of classifications of Las Vegas, Nevada
Project 3: On your own
Module 8 - Urban change
Project 1: Measuring urban change in Loudoun County, Virginia
Project 2: Measuring urban change in Las Vegas, Nevada
Project 3: On your own
Module 9 - Water
Project 1: Measuring the impact of drought on Texas reservoirs
Project 2: Measuring Minnesota lake temperature using thermal infrared data
Project 3: On your own
Module 10 - Normalized Difference Vegetation Index
Project 1: Using NDVI to study drought conditions in Texas
Project 2: Using NDVI to study seasonal change in Minnesota
Project 3: On your own
Appendix A: Downloading Landsat imagery
Appendix B: References
Appendix C: Image and data credits
Appendix D: Data license agreement
Appendix E: Installing the data and software