Click to have a closer look
About this book
About this book
The field of accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book published in 1999. As a result, this much-anticipated new edition was significantly expanded and enhanced to reflect growth in the field.
This revision includes four new chapters on such topics as positional accuracy and using accuracy assessment as an intermediate step in image classification. Additionally, the authors devote an entire chapter to the fuzzy accuracy assessment process and include a 16-page color insert. A new case study represents current complications and issues of interest, while a new order of chapters makes the presentation more effective.
Introduction 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_
University of New Hampshire, Durham, USA The Alta Vista Company, Berkeley, California, USA