ABSTRACT

During the post-classification for raster land cover updating, manual data inconsistency checking is labour-intensive and time-consuming. To address this issue, a spatial relationships-based data inconsistency detection method is proposed, which includes a model that represents the topological relations, a set of prejudgment rules, and a multiple-matching process for posteriori judgement. Taking GlobeLand30 five updated sheets of interest in 2015 for examples, data inconsistencies can be detected in approximately twenty minutes for each sheet, and the overall detection accuracy is 87.6%. After manual verification, the data quality is improved by 10.6%.

摘要

在栅格土地覆盖更新的后分类过程中，手动数据不一致检查既费力又耗时。针对这一问题，提出了一种基于空间关系的数据不一致检测方法，该方法包括表示拓扑关系的模型、一组预判规则和用于后验判断的多重匹配过程。以GlobeLand30 2015年更新的5张感兴趣的图纸为例，每张图纸大约20分钟即可检测出数据不一致的情况，总体检测准确率为87.6%。经过人工验证，数据质量提高了10.6%。