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Status of land cover classification accuracy assessment

计算机科学 专题地图 土地覆盖 混淆矩阵 遥感 过程(计算) 数据挖掘 数据科学 混乱 封面(代数) 土地利用 人工智能 地图学 地理 机械工程 土木工程 工程类 心理学 精神分析 操作系统
作者
Giles M. Foody
出处
期刊:Remote Sensing of Environment [Elsevier BV]
卷期号:80 (1): 185-201 被引量:4541
标识
DOI:10.1016/s0034-4257(01)00295-4
摘要

The production of thematic maps, such as those depicting land cover, using an image classification is one of the most common applications of remote sensing. Considerable research has been directed at the various components of the mapping process, including the assessment of accuracy. This paper briefly reviews the background and methods of classification accuracy assessment that are commonly used and recommended in the research literature. It is, however, evident that the research community does not universally adopt the approaches that are often recommended to it, perhaps a reflection of the problems associated with accuracy assessment, and typically fails to achieve the accuracy targets commonly specified. The community often tends to use, unquestioningly, techniques based on the confusion matrix for which the correct application and interpretation requires the satisfaction of often untenable assumptions (e.g., perfect coregistration of data sets) and the provision of rarely conveyed information (e.g., sampling design for ground data acquisition). Eight broad problem areas that currently limit the ability to appropriately assess, document, and use the accuracy of thematic maps derived from remote sensing are explored. The implications of these problems are that it is unlikely that a single standardized method of accuracy assessment and reporting can be identified, but some possible directions for future research that may facilitate accuracy assessment are highlighted.
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