Research On Identical Entity Geometric Matching In Multi-Source Spatial Data

The integration and updating of the geographic spatial data are the foreland of the international geography information science. Being the key technique of the spatial data integration and updating, spatial data matching is to establish the relationship of the geographic entities from multi-source databases and finally realize the comprehensive utilization of the multi-source data. By studying the related theory and arithmetic of the spatial data matching, the paper discussed the geometric matching for identical entities in multi-source spatial data. The main contents and conclusion include:1. Discussing the definition, characteristic, difference of spatial data and the relation to identical entity matching; Discussing and studying the definition, restricted conditions and technical flow of identical entity matching. It indicated that the spatial character and the attribute character of spatial data were the basement of identical entity matching, and the temporal character and map-restricted character are the root of identical entity matching. The limiting conditions of the identical entity matching include: the relation of the two matching source data-base should be equivalent or intersectant or inclusive.; the system difference of the two matching data-base should be removed and reach the state of form uniformity; the scale difference of the two matching data-base should not be too great; the temporal character of the two matching data-base should be the same or close. It indicated that identical entity matching included four steps: data preprocessing; map registration; identical entity matching; matching postprocessing.2. Studying the main content of the data preprocessing and map alignment which is the preconditions of identical entity matching, and mainly discussing the methods and the key awaiting solved problems of map alignment.3. Studying all kinds of arithmetic and their characteristics of identical entity matching in multi-source spatial data. Matching methods include geometric matching, topological matching and attribute matching. The paper discussed in detail the geometric matching of identical lines and areas.4. Based on an universal platform for digital map cartography of the prototype system (MapMaker soft), the paper experimented the 1:1 geometric matching of identical roads in the same scale vector maps by using the geometric similarities comparing matching arithmetic based on buffer, and experimented the n:m geometric matching of identical roads in multi-scale vector maps by using the distance of node to the broken line matching arithmetic based on buffer. The paper realized the simply automated extraction of water areas based on remote sensing images, and experimented the 1:1 and 1:n geometric matching of identical water areas from raster-vector maps in different periods. The paper analyzed and evaluated the matching effects of the arithmetic with different parameters.