Incorporating Reference Classification Uncertainty Into the Analysis of Land Cover Accuracy

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Abstract

To accommodate the difficulty of identifying a single 'true' or 'reference' class, the reference data protocol of an accuracy assessment may include identifying both a primary and alternate reference land cover label along with a rating of the interpreter's confidence in the reference classification obtained for each sample location. This additional reference information is used to construct a nominal variable (called CONF) in which the categories represent the 'confidence' in the correctness of the map land cover classification at a given location. An accuracy measure that incorporates uncertainty in the reference classification is then derived by assigning partial credit weights to each CONF class. Further, the accuracy reporting format can be organized by CONF classes to provide additional understanding of the relationship between accuracy and uncertainty in the reference classification. The analysis is illustrated using an accuracy assessment of a land cover map of Portugal. These analyses incorporating uncertainty in the reference classification are intended to supplement traditional analyses to further enhance understanding of the accuracy of land cover maps. © 2009 Taylor & Francis.

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Sarmento, P., Carrão, H., Caetano, M., & Stehman, S. V. (2009). Incorporating Reference Classification Uncertainty Into the Analysis of Land Cover Accuracy. International Journal of Remote Sensing, 30(20), 5309–5321. https://doi.org/10.1080/01431160903130994

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