Assessing the Accuracy of Remotely Sensed Data - Principles and Practices, Second Edition

Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. As a result, the much-anticipated new edition is significantly expanded and enhanced to reflect growth in the field. The new edition features three new chapters, including: Fuzzy accuracy assessment Positional accuracy Case study: Mapping land cover and land use in the Florida panhandle The authors provide a complete presentation of how to assess the positional accuracy of a map along with a discussion of the impact of positional accuracy on thematic accuracy. They also include a more thorough discussion of the special sampling issues that must be considered to effectively assess change. Complete with a 16-page color insert, this second edition continues to provide a complete guide to designing and conducting a state-of-the-art accuracy assessment.Table of ContentIntroduction Why Map? Why Assess the Accuracy of a Map? Types of Map Accuracy Assessment Critical Steps in Accuracy Assessment Organization of the Book The History of Map Accuracy Assessment How Maps Are Made History of Accuracy Assessment Positional Accuracy What Is Positional Accuracy? What Are the Common Standards for Positional Accuracy? Positional Accuracy Assessment Design and Sample Selection How Is Positional Accuracy Analyzed? Summary Appendix 3.1: Determining the Required Sample Size Thematic Accuracy Non-Site-Specific Assessments Site-Specific Assessments Sample Design Considerations What Are the Thematic Map Classes to Be Assessed? What Is the Appropriate Sample Unit? How Many Samples Should Be Taken? How Should the Samples Be Chosen? Final Considerations Reference Data Collection What Should Be the Source of the Reference Data? How Should the Reference Data Be Collected? When Should the Reference Data Be Collected? Ensuring Objectivity and Consistency Basic Analysis Techniques Kappa Margfit Conditional Kappa Weighted Kappa Compensation for Chance Agreement Confidence Limits Area Estimation/Correction Analysis of Differences in the Error Matrix Errors in the Reference Data Sensitivity of the Classification Scheme to Observer Variability Inappropriateness of the Remote Sensing Data Employed to Make the Map Mapping Error Summary Appendix 8.1: Wrangell-St. Elias National Park and Preserve: Land Cover Mapping Classification Key Fuzzy Accuracy Assessment Expanding the Major Diagonal of the Error Matrix Measuring Map Class Variability The Fuzzy Error Matrix Approach Summary Case Study Accuracy Assessment for the NOAA Next-Generation C-CAP Pilot Project Overview of the Case Study Design of the Accuracy Assessment Data Collection Analysis Lessons Learned Appendix 10.1: Decision Rules for the Classification Scheme Advanced Topics Change Detection Multilayer Assessments Appendix 11.1: Class Descriptions of the 2005 NLCD Land Cover Bibliography Index_Biographical NoteUniversity of New Hampshire, Durham, USA The Alta Vista Company, Berkeley, California, USA