{"id":"https://openalex.org/W2768435963","doi":"https://doi.org/10.1109/geoinformatics.2017.8090909","title":"Multiple sources geographic attribute data uncertainty and information fusion schemes","display_name":"Multiple sources geographic attribute data uncertainty and information fusion schemes","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2768435963","doi":"https://doi.org/10.1109/geoinformatics.2017.8090909","mag":"2768435963"},"language":"en","primary_location":{"id":"doi:10.1109/geoinformatics.2017.8090909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2017.8090909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th International Conference on Geoinformatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006671211","display_name":"Shanzhen Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shanzhen Yi","raw_affiliation_strings":["College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015171550","display_name":"Zhongqian Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongqian Tang","raw_affiliation_strings":["College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110533929","display_name":"Yangfan Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangfan Xiao","raw_affiliation_strings":["College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006671211"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22250592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9796000123023987,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.7964882850646973},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6458810567855835},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6313424110412598},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5953925848007202},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5617560744285583},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.5200805068016052},{"id":"https://openalex.org/keywords/geographic-information-system","display_name":"Geographic information system","score":0.5102493762969971},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.44112253189086914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.408780038356781},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22542977333068848},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16926690936088562},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.13650715351104736}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.7964882850646973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6458810567855835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6313424110412598},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5953925848007202},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5617560744285583},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.5200805068016052},{"id":"https://openalex.org/C41856607","wikidata":"https://www.wikidata.org/wiki/Q483130","display_name":"Geographic information system","level":2,"score":0.5102493762969971},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.44112253189086914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.408780038356781},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22542977333068848},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16926690936088562},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.13650715351104736},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/geoinformatics.2017.8090909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2017.8090909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th International Conference on Geoinformatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W117433747","https://openalex.org/W1157599955","https://openalex.org/W1510933668","https://openalex.org/W1568281349","https://openalex.org/W1581530725","https://openalex.org/W1599043334","https://openalex.org/W1971875039","https://openalex.org/W1977083296","https://openalex.org/W1979725639","https://openalex.org/W1994414501","https://openalex.org/W2000193830","https://openalex.org/W2033717735","https://openalex.org/W2036710343","https://openalex.org/W2048058569","https://openalex.org/W2049472359","https://openalex.org/W2054129669","https://openalex.org/W2076983043","https://openalex.org/W2086019442","https://openalex.org/W2096768134","https://openalex.org/W2100613188","https://openalex.org/W2101206561","https://openalex.org/W2107227749","https://openalex.org/W2110037957","https://openalex.org/W2119803205","https://openalex.org/W2168092187","https://openalex.org/W2194514055","https://openalex.org/W2484549398","https://openalex.org/W2499148359","https://openalex.org/W2499524267","https://openalex.org/W2503642504","https://openalex.org/W2917549735","https://openalex.org/W4229510723","https://openalex.org/W6604680331"],"related_works":["https://openalex.org/W1828158523","https://openalex.org/W2353179089","https://openalex.org/W2047547195","https://openalex.org/W204175656","https://openalex.org/W2923538289","https://openalex.org/W2353125546","https://openalex.org/W2470643824","https://openalex.org/W2911841387","https://openalex.org/W4400595174","https://openalex.org/W2803255289"],"abstract_inverted_index":{"There":[0],"are":[1,112,119,158,193],"many":[2],"methods":[3],"for":[4,13,41,85,121,154,186],"dealing":[5],"with":[6],"spatial":[7],"uncertainty.":[8],"However,":[9],"a":[10],"separate":[11],"discussion":[12],"attribute":[14,75,97,124,140,145,151],"uncertainty":[15,33,48,78,123],"of":[16,26,29,34,49,56,74,79,88,92,183],"geographic":[17,30,50,57,64,115],"information":[18,51,58,82,116,184],"is":[19,39,52],"still":[20],"rare.":[21],"With":[22],"the":[23,32,71],"rapid":[24],"development":[25],"multiple":[27,86],"sources":[28,87],"data,":[31],"attributes":[35,135],"and":[36,44,60,77,81,98,102,107,110,147,175,189],"their":[37,103],"fusion":[38,83,117,146,156,185],"important":[40,54],"accuracy":[42],"assessment":[43,192],"decision":[45,65,172],"making.":[46,66],"Attribute":[47],"an":[53,181],"aspect":[55],"quality":[59],"will":[61],"further":[62],"affect":[63],"This":[67],"paper":[68],"has":[69],"discussed":[70],"different":[72,155],"types":[73,91],"measurement":[76],"geo-data":[80],"schemes":[84,118,157],"geo-data.":[89],"Two":[90],"attributes,":[93],"i.e.":[94,105,126,160],"continuous":[95,134],"variable":[96,100],"categorical":[99,139],"attribute,":[101],"uncertainty,":[104],"random":[106],"error,":[108],"vagueness":[109],"ambiguity,":[111],"discussed.":[113,194],"Five":[114],"given":[120],"multi-sources":[122,129],"information,":[125],"(a)":[127],"univariate":[128],"data":[130],"fusion,":[131,136,141],"(b)":[132],"multivariate":[133,138,143,149,164],"(c)":[137],"(d)":[142],"normalized":[144],"(e)":[148],"continuous-category":[150],"fusion.":[152],"Methods":[153],"discussed,":[159],"maximum":[161],"likelihood":[162],"estimation,":[163],"regression,":[165],"Artificial":[166],"Neural":[167],"Network,":[168],"Dempster-Shafer":[169],"evidence,":[170],"multi-attribute":[171],"making":[173],"(MADA),":[174],"ordered":[176],"weighted":[177],"averaging":[178],"(OWA).":[179],"Finally":[180],"example":[182],"precipitation":[187],"estimation":[188],"flood":[190],"susceptibility":[191]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}