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Remote Sensing and GIS Accuracy Assessment - Chapter 17

So sánh bản đồ cơ bản trong viễn thám và phân tích dữ liệu không gian địa lý rộng phạm vi của các ứng dụng, bao gồm đánh giá tính chính xác, phát hiện thay đổi, và mô hình mô phỏng. Ứng dụng phổ biến bao gồm so sánh các bản đồ tham chiếu có nguồn gốc từ vệ tinh hình ảnh hoặc bản đồ của một cảnh quan thực tế kết quả đầu ra mô hình mô phỏng. | CHAPTER 17 Components of Agreement between Categorical Maps at Multiple Resolutions R. Gil Pontius Jr. and Beth Suedmeyer CONTENTS 17.1 Introduction.233 17.1.1 Map Comparison.233 17.1.2 Puzzle Example.234 17.2 Methods. .236 17.2.1 Example Data.236 17.2.2 Data Requirements and Notation.236 17.2.3 Minimum Function.239 17.2.4 Agreement Expressions and Information Components.239 17.2.5 Agreement and Disagreement.242 17.2.6 Multiple Resolutions.244 17.3 Results.245 17.4 Discussion.248 17.4.1 Common Applications.248 17.4.2 Quantity Information .249 17.4.3 Stratification and Multiple Resolutions.250 17.5 Conclusions.250 17.6 Summary .251 Acknowledgments .251 References .251 17.1 INTRODUCTION 17.1.1 Map Comparison Map comparisons are fundamental in remote sensing and geospatial data analysis for a wide range of applications including accuracy assessment change detection and simulation modeling. Common applications include the comparison of a reference map to one derived from a satellite image or a map of a real landscape to simulation model outputs. In either case the map that is 233 2004 by Taylor Francis Group LLC 234 REMOTE SENSING AND GIS ACCURACY ASSESSMENT considered to have the highest accuracy is used to evaluate the map of questionable accuracy. Throughout this chapter the term reference map refers to the map that is considered to have the highest accuracy and the term comparison map refers to the map that is compared to the reference map. Typically one wants to identify similarities and differences between the reference map and the comparison map. There are a variety of levels of sophistication by which to compare maps when they share a common categorical variable Congalton 1991 Congalton and Green 1999 . The simplest method is to compute the proportion of the landscape classified correctly. This method is an obvious first step however the proportion correct fails to inform the scientist of the most important ways in which the maps differ and hence it fails to .