顾及栅格空间拓扑关系的地表覆盖时空目标不一致性探测方法

地表覆盖与更新是地理国情监测、环境变化评估、生态系统保护等不可或缺的基础地理信息。遥感制图技术已成为地表覆盖信息提取的重要手段,但因地物光谱、纹理及时相等特征复杂性,地表覆盖更新数据往往存在错分、漏分,从而导致地表覆盖时空目标不一致。现有地表覆盖更新数据不一致性探测主要以人工检查为主、部分自动化为辅的方式,生产实践中需要大量的作业人员与时间,缺乏行之有效的不一致性自动化探测工具。本文研究分析了栅格地表覆盖更新数据不一致性检查面临的挑战,提出了基于复合逻辑量词的栅格空间拓扑关系计算方法、基于置信区间的更新期地表覆盖错分目标初判规则构建,以及利用空间约束多重匹配的更新期错分目标后验判断,形成了“关系-规则-判断”的地表覆盖时空目标不一致性探测体系。试验以山东临朐、垦利GlobeLand30数据为研究对象,经与统计一致性检核方法对比分析、参照真实地表影像数据,实现了地表覆盖时空目标不一致性探测与有效性检验,验证了探测方法可行性。

A topological relations-based inconsistency detection method for spatiotemporal land cover objects in raster space

Land cover updates are key datasets in geographic national conditions monitoring, environmental change assessment, and ecological system protection. Remote sensing technology has become an important tool for an update of land cover datasets. However, as the complexity of spectrum, texture and temporal characteristics, omission and commission errors usually occur in land cover data, leading to the issue of spatiotemporal land cover object inconsistency. Currently, detection of land cover data inconsistency gives priory to manual inspection, and partial automation is implemented. In practice, a huge of workmen and time are needed in data inconsistency detection, lacking of an automated detection tool. The challenge of land cover data inconsistency detection in raster space is analyzed in this study. A logic quantifiers-based topological relationships calculation in raster space, the initial-judgment rules construction based on confidence interval, and a post-judgement using spatial multi-matching are proposed, forming a "relation-rule-judgment" detection system. Inconsistency detection of the GlobeLand30 datasets is conducted in study areas of Linqu and Kenli, Shandong, China. Comparing with statistics inconsistency detection, and taking remote sensing images as reference, the effectiveness of inconsistent land cover objects detected in update is validated, and this method is proved to be practically feasible.