From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling
文献类型：期刊论文
| 作者 | Hou, Zhi-Wei3,4; Qin, Cheng-Zhi1,3,4 ; Zhu, A-Xing1,2,3,4,5; Liang, Peng3,4; Wang, Yi-Jie3,4; Zhu, Yun-Qiang1,3,4
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| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
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| 出版日期 | 2019-09-01 |
| 卷号 | 8期号:9页码:16 |
| 关键词 | geographic modeling input data preparation intelligent geoprocessing service composition |
| DOI | 10.3390/ijgi8090376 |
| 通讯作者 | Qin, Cheng-Zhi(qincz@lreis.ac.cn) |
| 英文摘要 | One of the key concerns in geographic modeling is the preparation of input data that are sufficient and appropriate for models. This requires considerable time, effort, and expertise since geographic models and their application contexts are complex and diverse. Moreover, both data and data pre-processing tools are multi-source, heterogeneous, and sometimes unavailable for a specific application context. The traditional method of manually preparing input data cannot effectively support geographic modeling, especially for complex integrated models and non-expert users. Therefore, effective methods are urgently needed that are not only able to prepare appropriate input data for models but are also easy to use. In this review paper, we first analyze the factors that influence data preparation and discuss the three corresponding key tasks that should be accomplished when developing input data preparation methods for geographic models. Then, existing input data preparation methods for geographic models are discussed through classifying into three categories: manual, (semi-)automatic, and intelligent (i.e., not only (semi-)automatic but also adaptive to application context) methods. Supported by the adoption of knowledge representation and reasoning techniques, the state-of-the-art methods in this field point to intelligent input data preparation for geographic models, which includes knowledge-supported discovery and chaining of data pre-processing functionalities, knowledge-driven (semi-)automatic workflow building (or service composition in the context of geographic web services) of data preprocessing, and artificial intelligent planning-based service composition as well as their parameter-settings. Lastly, we discuss the challenges and future research directions from the following aspects: Sharing and reusing of model data and workflows, integration of data discovery and processing functionalities, task-oriented input data preparation methods, and construction of knowledge bases for geographic modeling, all assisting with the development of an easy-to-use geographic modeling environment with intelligent input data preparation. |
| WOS关键词 | WEB SERVICES ; SEMANTIC WEB ; AUTOMATIC COMPOSITION ; ENVIRONMENTAL-MODELS ; DATA VISUALIZATION ; SOFTWARE PACKAGE ; SWAT MODEL ; GIS ; WATER ; FRAMEWORK |
| 资助项目 | National Natural Science Foundation of China[41431177] ; National Natural Science Foundation of China[41422109] ; Innovation Project of LREIS[O88RA20CYA] ; Vilas Associate Award ; Hammel Faculty Fellow Award ; Manasse Chair Professorship from the University of Wisconsin-Madison |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000488826400005 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; Innovation Project of LREIS ; Vilas Associate Award ; Hammel Faculty Fellow Award ; Manasse Chair Professorship from the University of Wisconsin-Madison |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/129928]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Qin, Cheng-Zhi |
| 作者单位 | 1.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 2.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 5.Nanjing Normal Univ, Sch Geog, Nanjing 210023, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hou, Zhi-Wei,Qin, Cheng-Zhi,Zhu, A-Xing,et al. From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(9):16. |
| APA | Hou, Zhi-Wei,Qin, Cheng-Zhi,Zhu, A-Xing,Liang, Peng,Wang, Yi-Jie,&Zhu, Yun-Qiang.(2019).From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(9),16. |
| MLA | Hou, Zhi-Wei,et al."From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.9(2019):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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