【摘要】 针对传统的地类图斑边界不一致检测及处理方法难以兼顾拓扑正确性、语义一致性、面积平衡性等多重约束条件，处理效果不佳，且通常需要人工干预，耗时较长等问题，提出一种基于拓扑分解模型的边界不一致检测与处理方法：构建拓扑分解模型，将图斑面数据转化为拓扑多边形，并降维生成代理点；定义4种边界不一致模式，根据代理点与原始图斑拓扑关系以及拓扑多边形组成弧段的语义信息进行模式识别；顾及语义相似度和空间邻近度指标，提出兼并法和剖分法对边界不一致模式进行修正。采用贵州省某县地类图斑实际数据进行实验验证，结果表明本文方法具有较高的边界不一致检测准确度，处理效率高且满足地类图斑质检要求。更多还原

【Abstract】 The traditional inconsistency detection and processing methods are difficult to take into account multiple constraints such as topology correctness, semantic consistency, and area balance, and they usually require manual intervention, which takes a long time. In view of this, an inconsistency detection and processing method for patch boundary based on topological decomposition model is proposed. First, the topological decomposition model was built, topological polygons were converted from patches, and the polygons were dimensionally reduced to agent points. Second, 4 boundary inconsistency patterns were defined, and they were recognized through the topological relationship between agent points and patches and the semantic information of the arcs which were composed of topological polygons. Finally, the merger method and the dissecting method were proposed to modify boundary inconsistency patterns, taking into account semantic similarity and space adjacent indicators. Experimental verification is carried out on the land-use data in Guizhou Province, and the result shows that this method has high accuracy and efficiency of inconsistency detection and processing for patch boundary, and the processing results meet the requirements of the quality inspection.更多还原