Researches And Applications On Polygon Entity Matching For Multi-scale Vector Data Based On Geometric Features

With the development and wide application Geographic Information System (hereinafter referred to as GIS) technology, integration and instant (quickly) updating of multi-source, multi-scale, multi-temporal spatial data, has become an inevitable trend quickly update and integration of applications. Thus quickly updating and sustainable development of GIS spatial database has become an urgent task, and the vector spatial data matching technology is the key issue to be addressed. Since Vector Spatial Data of the same region are usually repeatedly collected by a number of departments or the same departments but at different times, the data varies in the geometry position, geometry shape, topology structure, geometric accuracy, and level of attribute detail, coding schemes, semantic expression and the relationship between entity spaces. This makes the consolidation and sharing of the data become very difficult. In order to obtain spatial data of higher accuracy, richer attribute information and wider coverage of mapping with high quality, the procedure of entity matching is very necessary between different map databases to establish the relationship between entities. And on this basis, fusion of vector spatial data can be handled to solve geometric, topological, semantic inconsistencies between the data.This thesis makes thorough research on methods of entities matching, and explores changes of the surface entities features in a multi-scale and its matching methods. In Addition, this thesis illustrates applications of entities matching in the database updating. This thesis also proposes reasonable and feasible methods of multi-scale entities matching and schemes of element-level data updating.Firstly, according to differences of geometric features of surface vector data and type of vector elements, three geometric matching methods are designed, that is, orientation coding method, tangent space method and the discrete geometric moments. Orientation coding method applies for matching of simple and regular surface entities at small and medium scale (such as 1:50000 buildings, streets, etc.), with a high processing speed. In order to identify the geometric characteristics(features) of surface entities, while to maintain more information about the original attribute of the entities as possible, tangent space method(matching method on the tangent space) is proposed. This method expresses (projects) shapes of surface entities in the tangent space, and calculates geometric similarity with adaptive similarity of shapes. Experimental results show that describing surface entities in tangent plane, feature extraction method is simple with little memory, and the coding has the characteristics of shape invariance. Additionally, this methods obtains accurate matching when applied to complex surface entities at small and medium scales. When there is variance in scales (When there is a certain span of time scales), this thesis introduces improved shape invariant geometric moments to the process of matching. By adjusting the traditional discrete HU moment invariants based on image pixels to moments constructed by triangles witch are established by outline of surface entities, matching accuracy has been improved.Secondly, considering the span of a certain scale of one to one entity matching, hierarchical model of surface entities can be built with the Douglas-Peucker algorithm and angle calculation algorithm of entities, first extract the corresponding physical characteristics, and then a physical match and improve the matching accuracy. For one to many matches in multi-scale matching, this thesis puts forward a matching model based on clustering through expanding and contracting the buffer zone. This method extracts features of mathematical morphology operators and tangent space extract multiple surfaces merging algorithm outline entities attributes, and on this basis, geometric matching with the source matching entities will be performed.In addition, this thesis also researches on the basic topological relationship between surface entities, and in order to address the problem of unable to distinguish entities in geometric matching, a match method based on topological relationship of the overall environment is proposed. Topological matching happens according to the hierarchical relationship between the matching entities with the environment around. In the case of semantic multi-scale matching in multi-scale matching, semantic similarity is calculated through the establishment of semantic encoding and hierarchical properties of ontology structure and similarity of attributes, such as numeric and text strings can be calculated through the semantic relationship between entities.Finally, this thesis designs the whole processes of updating elemental database based on entity matching, and with index-based grid searching method, efficiency of searching candidate matching set during surface entities matching and efficiency of spatial analysis have been greatly improved. By adopting similarity calculation model based on weights and rule-based, surface entities matching problems in the complex situations with diverse elements are solved. Additionally, the similarity gained during the entities matching can be used to decide whether to update the database or not, and updated entities are settled down in historical database which facilitate elements management.