Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy
Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy
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DOI：
10.14358/pers.70.5.627
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发表时间：
2004-05-01
影响因子：
1.3
通讯作者：
Foody, GM
中科院分区：
文献类型：
--
作者：
Foody, GM
在遥感研究中，经常比较通过图像分类分析得到的专题地图的精度。这种比较通常是通过对观察到的准确性差异的基本主观评估来实现的，但应该以统计上严格的方式进行。在遥感研究中广泛使用的一种评估地图精度差异的统计显著性的方法是基于对每张地图得出的一致性kappa系数的比较。比较kappa系数的传统方法假定其计算中使用的样本是独立的，这一假设通常是不满足的，因为每幅地图经常使用一些地面数据站点的样本。对于相关样本和独立样本，可采用其他方法来评估准确性差异的统计显著性。讨论了基于kappa系数和正确分配案例比例的地图比较方法，这是遥感中最广泛使用的两个主题拖地精度指标。一个例子说明了如何严格比较基于一些地面数据站点样本的分类，并突出了在比较分类准确性陈述时区分单方统计检验和双边统计检验的重要性。
The accuracy of thematic maps derived by image classification analyses is often compared in remote sensing studies. This comparison is typically achieved by a basic subjective assessment of the observed difference in accuracy but should be undertaken in a statistically rigorous fashion. One approach for the evaluation of the statistical significance of a difference in map accuracy that has been widely used in remote sensing research is based on the comparison of the kappa coefficient of agreement derived for each map. The conventional approach to the comparison of kappa coefficients assumes that the samples used in their calculation are independent, an assumption that is commonly unsatisfied because the some sample of ground data sites is often used for each map. Alternative methods to evaluate the statistical significance of differences in accuracy are available for both related and independent samples. Approaches for map comparison based on the kappa coefficient and proportion of correctly allocated cases, the two most widely used metrics of thematic mop accuracy in remote sensing, are discussed. An example illustrates how classifications based on the some sample of ground data sites may be compared rigorously and highlights the importance of distinguishing between one- and two-sided statistical tests in the comparison of classification accuracy statements.