{"id":"https://openalex.org/W2156090036","doi":"https://doi.org/10.1109/igarss.2005.1525780","title":"Extracting city information in tm image using mixed decision tree method","display_name":"Extracting city information in tm image using mixed decision tree method","publication_year":2005,"publication_date":"2005-11-15","ids":{"openalex":"https://openalex.org/W2156090036","doi":"https://doi.org/10.1109/igarss.2005.1525780","mag":"2156090036"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2005.1525780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2005.1525780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05.","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":null,"display_name":"Wang Peijuan","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang Peijuan","raw_affiliation_strings":["Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhu Qijiang","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu Qijiang","raw_affiliation_strings":["Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xie Donghui","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xie Donghui","raw_affiliation_strings":["Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Remote Sensing and GIS, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13690727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":null,"first_page":"3963","last_page":"3966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980000257492065,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/decision-tree","display_name":"Decision tree","score":0.6477118134498596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6278712153434753},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49264460802078247},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4839404225349426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4250427782535553},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42373210191726685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35835590958595276},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33779484033584595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17144736647605896},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07020452618598938}],"concepts":[{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6477118134498596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6278712153434753},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49264460802078247},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4839404225349426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4250427782535553},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42373210191726685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35835590958595276},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33779484033584595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17144736647605896},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07020452618598938}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2005.1525780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2005.1525780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1968229544","https://openalex.org/W1974771415","https://openalex.org/W1998902551","https://openalex.org/W2042809130","https://openalex.org/W2044023201","https://openalex.org/W2114828048","https://openalex.org/W2136036783","https://openalex.org/W2153633422","https://openalex.org/W2158864811","https://openalex.org/W2166917517","https://openalex.org/W2381370052","https://openalex.org/W2763134324"],"related_works":["https://openalex.org/W2476864898","https://openalex.org/W40494022","https://openalex.org/W77690704","https://openalex.org/W4213017374","https://openalex.org/W4241519009","https://openalex.org/W2971758332","https://openalex.org/W2377198601","https://openalex.org/W2381980924","https://openalex.org/W2353774927","https://openalex.org/W2081026125"],"abstract_inverted_index":{"As":[0,58],"traditional":[1],"classification":[2,138,141],"methods":[3],"use":[4],"spectrum":[5],"of":[6,70,80,84,158],"objects":[7,14,25,39],"only,":[8],"they":[9,20],"cannot":[10],"distinct":[11],"the":[12,23,30,37,78,102,122,128,137],"same":[13],"with":[15,29],"different":[16,24,38],"spectrum,":[17],"and":[18,46,114,117,147],"sometimes":[19],"will":[21],"misclass":[22],"into":[26,132],"one":[27],"class":[28,100],"similar":[31],"spectrum.":[32],"In":[33],"order":[34],"to":[35,135,145],"classify":[36],"correctly,":[40],"Mixed":[41],"Decision":[42],"Tree":[43],"(MDT)":[44],"method":[45,161],"Minimum":[47],"Distance":[48],"Texture":[49],"Feature":[50],"Vector":[51],"(MDTFV)":[52],"are":[53,119,130],"presented":[54],"in":[55,64,73,121],"this":[56],"paper.":[57],"a":[59,99],"case":[60],"study,":[61],"TM":[62],"image":[63,134],"Beijing":[65],"City,":[66],"including":[67,106],"some":[68],"parts":[69],"northern":[71],"suburban":[72],"China,":[74],"is":[75,143,153],"selected.":[76],"Considering":[77],"particularity":[79],"big":[81],"city,":[82],"lots":[83],"mixed":[85,96],"pixels":[86,93,97],"exist,":[87],"we":[88],"recognize":[89],"not":[90],"only":[91],"pure":[92],"but":[94],"also":[95],"as":[98],"for":[101],"result.":[103],"Eight":[104],"classes,":[105],"forest,":[107],"grass,":[108],"farm,":[109],"water,":[110],"building,":[111],"useless,":[112],"building":[113],"vegetation,":[115,118],"useless":[116],"gotten":[120],"research":[123],"region.":[124],"At":[125],"last":[126],"all":[127],"classes":[129],"overlaid":[131],"an":[133],"get":[136],"map.":[139],"The":[140],"accuracy":[142],"up":[144],"97.25%":[146],"Kappa":[148],"coefficient":[149],"reaches":[150],"0.9612,":[151],"which":[152],"improved":[154],"greatly":[155],"than":[156],"that":[157],"using":[159],"spectral":[160],"only.":[162]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
