Abstract:

The large-scale urban city is one of the most active elements, and has become one of the major tasks of spatial data updating. For the complex geometry shape, large amount of data-intensive, spatial data matching of polygon is still one of the most difficult problems to be solved. First, both the original polygon habitations and habitations to be matched were transformed into the main skeleton lines with reducing-dimension technique, and each of the skeleton line must reflect corresponding polygon’s outside characteristics. Second, the skeleton lines were translated into geometry morphological lines which were easier to express skeleton lines’ shape characteristics than skeleton lines themselves by additional interpolation calculation. Third, the correlation coefficient of the original habitation and habitation to be matched was achieved by Fourier transform, with which, the matching relationships of original polygon habitations and habitations to be matched were got. After transforming the two dimensional polygons into one dimensional skeleton lines, the complex of the habitations was reduced greatly on the one hand, and many algorithms for line could be cited on the other hand. After transforming the skeleton lines into morphological lines, and analyzing the shapes of original polygon habitations and habitations to be matched with Fourier transform, the spatial features’ geometry similar was improved greatly, which made great progress to the accuracy of spatial data matching. Examples illustrate the validity and scientificity.

Key words: habitation, reducing-dimension, sketch line, matching, the Fourier transform, the correlation coefficient