Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood
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 rela...
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doaj-17e5ef7e27fa49c283ce497076867c5c2020-11-24T21:54:46ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/278754278754Multiscale Feature Model for Terrain Data Based on Adaptive Spatial NeighborhoodHuijie Zhang0Yun Ma1Zhiqiang Ma2Xinting He3Yaxin Liu4Zijun Feng5School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaSchool of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, ChinaMultiresolution 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.http://dx.doi.org/10.1155/2013/278754 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Huijie Zhang Yun Ma Zhiqiang Ma Xinting He Yaxin Liu Zijun Feng |
spellingShingle |
Huijie Zhang Yun Ma Zhiqiang Ma Xinting He Yaxin Liu Zijun Feng Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood Mathematical Problems in Engineering |
author_facet |
Huijie Zhang Yun Ma Zhiqiang Ma Xinting He Yaxin Liu Zijun Feng |
author_sort |
Huijie Zhang |
title |
Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood |
title_short |
Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood |
title_full |
Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood |
title_fullStr |
Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood |
title_full_unstemmed |
Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood |
title_sort |
multiscale feature model for terrain data based on adaptive spatial neighborhood |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2013/278754 |
work_keys_str_mv |
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