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An approach to quality validation of large-scale data from the Chinese Flash Flood Survey and Evaluation (CFFSE)
Yuan, Ximin1; Liu, Yesen1; Huang, Yaohuan2; Tian, Fuchang1
2017-11-01
Source PublicationNATURAL HAZARDS
ISSN0921-030X
Volume89Issue:2Pages:693-704
Corresponding AuthorLiu, Yesen(ysliu@lreis.ac.cn)
AbstractQuality control of large-scale flash flood survey and evaluation data is vital and refers to various social and natural factors. In this study, we present a quality validation approach that uses a data model, Anselin Local Moran's I (DM-Moran), which is based on a model of the flash flood data and a spatial data mining algorithm. The approach of the DM-Moran model involves examining logical relationships and detecting anomalous survey units, which effectively integrates the advantages of certainty rules and checking for reasonableness. It resolves the inconsistencies in massive amounts of flash flood survey data that result from inconsistencies. We used the DM-Moran model to validate the quality of the data of the Chinese Flash Flood Survey and Evaluation (CFFSE) project. The kappa coefficients of the two steps of this approach were 0.95 and 0.99, which meet the requirements of the CFFSE project. We consider the DM-Moran model an effective approach to checking the quality of various other large-scale disaster datasets.
KeywordFlash flood Survey and evaluation Data quality validation DM-Moran model Spatial data mining
DOI10.1007/s11069-017-2986-0
WOS KeywordAGREEMENT ; KAPPA
Indexed BySCI
Language英语
Funding ProjectNational Key R&D Program of China[2017YFC0405601] ; Fund for Key Research Area Innovation Groups of China Ministry of Science and Technology[2014RA4031] ; Science Fund for Creative Research Groups of the National Natural Science Foundation of China[51621092] ; Program of Introducing Talents of Discipline to Universities[B14012]
Funding OrganizationNational Key R&D Program of China ; Fund for Key Research Area Innovation Groups of China Ministry of Science and Technology ; Science Fund for Creative Research Groups of the National Natural Science Foundation of China ; Program of Introducing Talents of Discipline to Universities
WOS Research AreaGeology ; Meteorology & Atmospheric Sciences ; Water Resources
WOS SubjectGeosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS IDWOS:000412556000010
PublisherSPRINGER
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/62143
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Yesen
Affiliation1.Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Yuan, Ximin,Liu, Yesen,Huang, Yaohuan,et al. An approach to quality validation of large-scale data from the Chinese Flash Flood Survey and Evaluation (CFFSE)[J]. NATURAL HAZARDS,2017,89(2):693-704.
APA Yuan, Ximin,Liu, Yesen,Huang, Yaohuan,&Tian, Fuchang.(2017).An approach to quality validation of large-scale data from the Chinese Flash Flood Survey and Evaluation (CFFSE).NATURAL HAZARDS,89(2),693-704.
MLA Yuan, Ximin,et al."An approach to quality validation of large-scale data from the Chinese Flash Flood Survey and Evaluation (CFFSE)".NATURAL HAZARDS 89.2(2017):693-704.
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