{"id":"https://openalex.org/W2904982494","doi":"https://doi.org/10.1109/geoinformatics.2018.8557179","title":"A Lake Selection Method Based on Dynamic Multi-Scale Clustering","display_name":"A Lake Selection Method Based on Dynamic Multi-Scale Clustering","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2904982494","doi":"https://doi.org/10.1109/geoinformatics.2018.8557179","mag":"2904982494"},"language":"en","primary_location":{"id":"doi:10.1109/geoinformatics.2018.8557179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2018.8557179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th 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/A5056026082","display_name":"Duan Peixiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Duan Peixiang","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024762618","display_name":"Haizhong Qian","orcid":"https://orcid.org/0000-0002-8125-7750"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Haizhong","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068437966","display_name":"HE Haiwei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He Haiwei","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017502310","display_name":"Xie Limin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie Limin","raw_affiliation_strings":["Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Cartography, Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056026082"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.14620046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.681390643119812},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.637076199054718},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6279832720756531},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.596543550491333},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38411882519721985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3359205722808838},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08604192733764648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681390643119812},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.637076199054718},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6279832720756531},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.596543550491333},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38411882519721985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3359205722808838},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08604192733764648},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/geoinformatics.2018.8557179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/geoinformatics.2018.8557179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th International Conference on Geoinformatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2036267401","https://openalex.org/W2324238275","https://openalex.org/W2382663514"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W2158836806","https://openalex.org/W2393816671","https://openalex.org/W2083665254","https://openalex.org/W2942177010"],"abstract_inverted_index":{"Current":[0],"lake":[1,48,73,85,132,166],"selection":[2,49,96,106,148],"methods":[3],"mostly":[4],"uses":[5],"the":[6,20,29,35,59,64,71,75,79,84,95,104,109,119,131,142,147,155,158,165,170,174],"form":[7],"of":[8,28,40,122,139,144,151,164,172],"selecting":[9],"as":[10],"a":[11,47,136],"whole,":[12],"and":[13,25,33,38,102,161],"are":[14,115],"difficult":[15],"to":[16,62,83,87,118],"take":[17],"into":[18,89],"account":[19],"attribute":[21],"characteristics,":[22],"distribution":[23],"characteristics":[24,27],"topological":[26],"lake.":[30],"By":[31],"analyzing":[32],"imitating":[34],"cognitive":[36],"behavior":[37],"process":[39],"artificial":[41],"lakes":[42,65,114,145],"selection,":[43],"this":[44],"paper":[45],"proposes":[46],"method":[50,156],"based":[51],"on":[52],"dynamic":[53,80],"multiscale":[54],"clustering.":[55],"First,":[56],"we":[57],"set":[58],"area":[60],"threshold":[61],"select":[63,70],"with":[66,91,135],"large":[67,137],"area,":[68],"then":[69,77],"\u201cisolated\u201d":[72],"through":[74],"buffer,":[76],"utilize":[78],"multi-scale":[81],"clustering":[82],"group":[86,133,167],"divide":[88],"areas":[90],"different":[92,105,110],"density,":[93],"decide":[94],"numbers":[97],"by":[98,125],"square":[99],"root":[100],"law":[101],"adopt":[103],"strategy":[107],"for":[108],"areas,":[111],"among":[112],"which":[113],"selected":[116],"according":[117],"comprehensive":[120],"evaluation":[121],"importance":[123],"calculated":[124],"iterative":[126],"principal":[127],"component":[128],"analysis":[129],"in":[130],"class":[134],"number":[138,143],"features":[140],"until":[141],"reaches":[146],"number.":[149],"Contrast":[150],"experiments":[152],"show":[153],"that":[154],"maintains":[157],"morphological":[159],"structure":[160],"density":[162],"contrast":[163],"effectively,":[168],"under":[169],"premise":[171],"considering":[173],"importance.":[175]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
