An improved HASM method for dealing with large spatial data sets
文献类型：期刊论文
| 作者 | Zhao, Na2,3,4; Yue, Tianxiang2,3,4; Chen, Chuanfa1; Zhao, Miaomiao2,4; Du, Zhengping2 |
| 刊名 | SCIENCE CHINA-EARTH SCIENCES
 |
| 出版日期 | 2018-08-01 |
| 卷号 | 61期号:8页码:1078-1087 |
| 关键词 | Surface modeling HASM Large spatial data |
| ISSN号 | 1674-7313 |
| DOI | 10.1007/s11430-017-9205-1 |
| 通讯作者 | Zhao, Na(zhaon@lreis.ac.cn) |
| 英文摘要 | Surface modeling with very large data sets is challenging. An efficient method for modeling massive data sets using the high accuracy surface modeling method (HASM) is proposed, and HASM_Big is developed to handle very large data sets. A large data set is defined here as a large spatial domain with high resolution leading to a linear equation with matrix dimensions of hundreds of thousands. An augmented system approach is employed to solve the equality-constrained least squares problem (LSE) produced in HASM_Big, and a block row action method is applied to solve the corresponding very large matrix equations. A matrix partitioning method is used to avoid information redundancy among each block and thereby accelerate the model. Experiments including numerical tests and real-world applications are used to compare the performances of HASM_Big with its previous version, HASM. Results show that the memory storage and computing speed of HASM_Big are better than those of HASM. It is found that the computational cost of HASM_Big is linearly scalable, even with massive data sets. In conclusion, HASM_Big provides a powerful tool for surface modeling, especially when there are millions or more computing grid cells. |
| WOS关键词 | SURFACE MODELING METHOD ; PRECONDITIONED CONJUGATE-GRADIENT ; INTERPOLATION METHODS ; DEM CONSTRUCTION ; PRECIPITATION ; CHINA ; CONVERGENCE ; ALGORITHMS ; ELEVATION ; RAINFALL |
| 资助项目 | National Natural Science Foundation of China[41541010] ; National Natural Science Foundation of China[41701456] ; National Natural Science Foundation of China[41421001] ; National Natural Science Foundation of China[41590840] ; National Natural Science Foundation of China[91425304] ; Key Programs of the Chinese Academy of Sciences[QYZDY-SSW-DQC007] ; Cultivate Project of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences[TSYJS03] |
| WOS研究方向 | Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:000440139000007 |
| 出版者 | SCIENCE PRESS |
| 资助机构 | National Natural Science Foundation of China ; Key Programs of the Chinese Academy of Sciences ; Cultivate Project of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/54570]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhao, Na |
| 作者单位 | 1.Shandong Univ Sci & Technol, Geomat Coll, Qingdao 266510, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Na,Yue, Tianxiang,Chen, Chuanfa,et al. An improved HASM method for dealing with large spatial data sets[J]. SCIENCE CHINA-EARTH SCIENCES,2018,61(8):1078-1087. |
| APA | Zhao, Na,Yue, Tianxiang,Chen, Chuanfa,Zhao, Miaomiao,&Du, Zhengping.(2018).An improved HASM method for dealing with large spatial data sets.SCIENCE CHINA-EARTH SCIENCES,61(8),1078-1087. |
| MLA | Zhao, Na,et al."An improved HASM method for dealing with large spatial data sets".SCIENCE CHINA-EARTH SCIENCES 61.8(2018):1078-1087. |
入库方式： OAI收割
来源：地理科学与资源研究所
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