Abstract
No thematic map is perfect. Some pixels or polygons are not accurately classified, no matter how well the map is crafted. Therefore, thematic maps need metadata that sufficiently characterize the nature and degree of these imperfections. To decision-makers, an accuracy assessment helps judge the risks of using imperfect geospatial data. To analysts, an accuracy assessment helps describe the reliability of the map for geospatial analyses and modeling, and the distribution of different types of “true” land cover within each mapped category. To producers of thematic maps, an accuracy assessment measures the degree of technical success for alternative algorithms or techniques. To project managers, an accuracy assessment helps determine contract compliance or measure performance of technical staff.
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References
Campbell, J.B. (1996). Introduction to Remote Sensing (2rd ed.). Guilford Press, New York.
Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons, New York.
Congalton, R. G. (1991). A review of accessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.
Czaplewski, R. L. (1992). Misclassification bias in areal estimates. Photogrammetric Engineering and Remote Sensing, 58, 189–192
Czaplewski, R. L. (1994). Variance approximations for assessments of classification accuracy. Research Paper RM-316. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.
Czaplewski, R. L., & Catts, G. P. (1992). Calibration of remotely sensed proportion or area estimates for misclassification error. Remote Sensing of Environment, 39, 29–43.
Czaplewski, R. L. (2000). Accuracy assessments and areal estimates using two-phase stratified random sampling, cluster plots, and the multivariate composite estimator. Quantifying Spatial Uncertainty in Natural Resources: Theory and Applications for GIS and Remote Sensing, 79–100. Ann Arbor Press, Chelsea, MI.
Gopal, S., & Woodcock, C. (1994). Theory and methods for accuracy assessment of thematic maps using fuzzy-sets. Photogrammetric Engineering and Remote Sensing, 60, 181–188.
Hudson, W. D., & Ramm, C. W. (1987). Correct formulation of the kappa coefficient of agreement. Photogrammetric Engineering and Remote Sensing, 53, 421–422.
Lloyd, C. J. (1999) Statistical Analysis of Categorical Data (3rd ed.). John Wiley & Sons, New York.
Lohr, S. L. (1999). Sampling: Design and Analysis. Brooks/Cole Publishing, Pacific Grove, CA.
Salant, P., & Dillman, D. A. (1994). How to conduct your own survey. John Wiley & Sons, New York.
Särndal, C. -E., Swensson, B., & Wretman, J. (1992). Model-assisted survey sampling. Springer-Verlag, New York.
Schreuder, H. T., Gregoire, T. G., & Wood, G. (1993) Sampling methods for multiresource forest inventory. John Wiley & Sons, New York.
Stehman, S.V. (1996), Estimating the kappa coefficient and its variance under stratified random sampling, Photogrammetric Engineering and Remote Sensing, 62, 401–407.
Stehman, S.V. (2002). Response to letter by G. Turk on chance correction and map evaluation. Remote Sensing of Environment, 82, 4.
Stehman, S. V., & Czaplewski, R. L. (1998). Design and analysis for thematic map accuracy assessment: fundamental principles. Remote Sensing of Environment, 64, 331–344.
Stehman, S. V. (2001). Statistical rigor and practical utility in thematic map accuracy assessment. Photogrammetric Engineering and Remote Sensing, 67, 727–734.
Story, M., & Congalton, R. G. (1986). Accuracy assessment: a user’s perspective. Photogrammetric Engineering and Remote Sensing, 52,397–399.
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Czaplewski, R.L. (2003). Accuracy Assessment of Maps of Forest Condition. In: Wulder, M.A., Franklin, S.E. (eds) Remote Sensing of Forest Environments. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0306-4_5
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DOI: https://doi.org/10.1007/978-1-4615-0306-4_5
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