| Li Xiaohua（李晓华）* **,Guo Mingqiang***,Qi Xinhong**.[J].高技术通讯(英文),2020,26(4):455~459 |
|
| A spatial decomposition approach for accelerating buffer analysis of vector data |
| |
| DOI：doi：10.3772/j.issn.1006-6748.2020.04.014 |
| 中文关键词: |
| 英文关键词: high performance spatial computing, buffer analysis, parallel computing, load balancing, vector data |
| 基金项目: |
| Author Name | Affiliation | | Li Xiaohua（李晓华）* ** | (*School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, P.R.China)
(**Guizhou Coal Mine Design Research Institute Co., Ltd, Guiyang 550025, P.R.China) | | Guo Mingqiang*** | (***School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, P.R.China) | | Qi Xinhong** | (**Guizhou Coal Mine Design Research Institute Co., Ltd, Guiyang 550025, P.R.China) |
|
| Hits: 1480 |
| Download times: 1343 |
| 中文摘要: |
| |
| 英文摘要: |
| Parallel vector buffer analysis approaches can be classified into 2 types: algorithm-oriented parallel strategy and the data-oriented parallel strategy. These methods do not take its applicability on the existing geographic information systems(GIS) platforms into consideration. In order to address the problem, a spatial decomposition approach for accelerating buffer analysis of vector data is proposed. The relationship between the number of vertices of each feature and the buffer analysis computing time is analyzed to generate computational intensity transformation functions (CITFs). Then, computational intensity grids (CIGs) of polyline and polygon are constructed based on the relative CITFs. Using the corresponding CIGs, a spatial decomposition method for parallel buffer analysis is developed. Based on the computational intensity of the features and the sub-domains generated in the decomposition, the features are averagely assigned within the sub-domains into parallel buffer analysis tasks for load balance. Compared with typical regular domain decomposition methods, the new approach accomplishes greater balanced decomposition of computational intensity for parallel buffer analysis and achieves near-linear speedups. |
|
View Full Text
View/Add Comment Download reader |
| Close |
|
|
|
