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Mathematical Problems in Engineering
Volume 2013, Article ID 278754, 12 pages
Research Article

Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood

1School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
2Key Laboratory of Intelligent Information Processing of Jilin Universities, Changchun 130117, China

Received 10 July 2013; Accepted 18 August 2013

Academic Editor: William Guo

Copyright © 2013 Huijie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Multiresolution hierarchy based on features (FMRH) has been applied in the field of terrain modeling and obtained significant results in real engineering. However, it is difficult to schedule multiresolution data in FMRH from external memory. This paper proposed new multiscale feature model and related strategies to cluster spatial data blocks and solve the scheduling problems of FMRH using spatial neighborhood. In the model, the nodes with similar error in the different layers should be in one cluster. On this basis, a space index algorithm for each cluster guided by Hilbert curve is proposed. It ensures that multi-resolution terrain data can be loaded without traversing the whole FMRH; therefore, the efficiency of data scheduling is improved. Moreover, a spatial closeness theorem of cluster is put forward and is also proved. It guarantees that the union of data blocks composites a whole terrain without any data loss. Finally, experiments have been carried out on many different large scale data sets, and the results demonstrate that the schedule time is shortened and the efficiency of I/O operation is apparently improved, which is important in real engineering.