Overselling overall map accuracy misinforms about research reliability

被引:54
作者
Shao, Guofan [1 ]
Tang, Lina [2 ]
Liao, Jiangfu [3 ]
机构
[1] Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA
[2] Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen 361021, Fujian, Peoples R China
[3] Jimei Univ, Coll Comp Engn, 185 Yinjiang Rd, Xiamen 361021, Fujian, Peoples R China
基金
中国国家自然科学基金; 美国食品与农业研究所; 国家重点研发计划;
关键词
Image processing; Error propagation; Imbalanced classes; Map accuracy; Comprehensive assessment;
D O I
10.1007/s10980-019-00916-6
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Context Image classification is routine in a variety of disciplines, and analysts rely on accuracy metrics to evaluate the resulting maps. The most frequently used accuracy metric in Earth resource remote sensing is overall accuracy. However, the inherent properties of this accuracy metric make it inappropriate as the single metric for map assessment, particularly when a map contains imbalanced categories. Objectives We discuss four noteworthy problems with overall accuracy. Under circumstances frequently encountered, overall accuracy is misleading or misinterpreted. Methods Literature review, hypothetical examples, and mathematic equations are used to prove overall accuracy is a poor general indicator of map quality. Conclusions Any research that involves classification techniques or a map product that is evaluated only with overall accuracy may be unreliable. It is necessary for map providers to publish the error matrix and its development procedure so that map users can computer whatever metrics as they wish.
引用
收藏
页码:2487 / 2492
页数:6
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