To meet different level requirements of train positioning and control, the track map data for train control consists of private data, track data and terrain environment data, and the track data are divided into feature layer and interpolation layer under different scales, which could contribute to complete structure of the track map. Finally, we prove the proposed method and achieved results to be effective and reasonable with sample data at county level. Based on statistic analysis, we then generate both macro and micro control rules for land use data generalization at various spatial scales and land use patterns. To quantitatively relate the indices and scale and landscape pattern metrics, land use data samples have been collected at multiple spatial scales in various land use regions across China.
We discuss the macro and micro indices of land use data generalization with consideration of spatial scales and landscape pattern. This paper studies the index system of land use data generalization from both scale and landscape pattern perspective. A second problem is general ignorance of landscape pattern. Firstly, determination of threshold values for multi-scale land use data generalization in a large area, such as a nation, remains subjective. Previous research suffers from two major setbacks.
Indices for land use data generalization are critical for generating multiscale land use maps and databases.
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