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Open AccessArticle

Thematic Classification Accuracy Assessment with Inherently Uncertain Boundaries: An Argument for Center-Weighted Accuracy Assessment Metrics

Department of Geology and Geography, West Virginia University, Morgantown, WV 26506, USA
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Remote Sens. 2020, 12(12), 1905; https://doi.org/10.3390/rs12121905
Received: 7 May 2020 / Revised: 5 June 2020 / Accepted: 10 June 2020 / Published: 12 June 2020
(This article belongs to the Section Remote Sensing Image Processing)
Accuracy assessment is one of the most important components of both applied and research-oriented remote sensing projects. For mapped classes that have sharp and easily identified boundaries, a broad array of accuracy assessment methods has been developed. However, accuracy assessment is in many cases complicated by classes that have fuzzy, indeterminate, or gradational boundaries, a condition which is common in real landscapes; for example, the boundaries of wetlands, many soil map units, and tree crowns. In such circumstances, the conventional approach of treating all reference pixels as equally important, whether located on the map close to the boundary of a class, or in the class center, can lead to misleading results. We therefore propose an accuracy assessment approach that relies on center-weighting map segment area to calculate a variety of common classification metrics including overall accuracy, class user’s and producer’s accuracy, precision, recall, specificity, and the F1 score. This method offers an augmentation of traditional assessment methods, can be used for both binary and multiclass assessment, allows for the calculation of count- and area-based measures, and permits the user to define the impact of distance from map segment edges based on a distance weighting exponent and a saturation threshold distance, after which the weighting ceases to grow. The method is demonstrated using synthetic and real examples, highlighting its use when the accuracy of maps with inherently uncertain class boundaries is evaluated. View Full-Text
Keywords: thematic image classification; thematic accuracy assessment; error matrix; error; uncertainty thematic image classification; thematic accuracy assessment; error matrix; error; uncertainty
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MDPI and ACS Style

Maxwell, A.E.; Warner, T.A. Thematic Classification Accuracy Assessment with Inherently Uncertain Boundaries: An Argument for Center-Weighted Accuracy Assessment Metrics. Remote Sens. 2020, 12, 1905. https://doi.org/10.3390/rs12121905

AMA Style

Maxwell AE, Warner TA. Thematic Classification Accuracy Assessment with Inherently Uncertain Boundaries: An Argument for Center-Weighted Accuracy Assessment Metrics. Remote Sensing. 2020; 12(12):1905. https://doi.org/10.3390/rs12121905

Chicago/Turabian Style

Maxwell, Aaron E.; Warner, Timothy A. 2020. "Thematic Classification Accuracy Assessment with Inherently Uncertain Boundaries: An Argument for Center-Weighted Accuracy Assessment Metrics" Remote Sens. 12, no. 12: 1905. https://doi.org/10.3390/rs12121905

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