{"id":"https://openalex.org/W2983763312","doi":"https://doi.org/10.1109/igarss.2019.8899029","title":"Road Material Information Extraction Based on Multi-Feature Fusion of Remote Sensing Image","display_name":"Road Material Information Extraction Based on Multi-Feature Fusion of Remote Sensing Image","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2983763312","doi":"https://doi.org/10.1109/igarss.2019.8899029","mag":"2983763312"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","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/A5100749336","display_name":"Chao Yang","orcid":"https://orcid.org/0000-0003-2417-0621"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Yang","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736194","display_name":"Yuxia Li","orcid":"https://orcid.org/0000-0001-7154-3641"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxia Li","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026744328","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0002-8539-180X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Peng","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102002813","display_name":"Yuan Cheng","orcid":"https://orcid.org/0000-0002-1662-3195"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Cheng","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017195934","display_name":"Ling Tong","orcid":"https://orcid.org/0000-0003-1883-7792"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Tong","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100749336"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.7349,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71749148,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"smc 3","issue":null,"first_page":"3943","last_page":"3946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9970999956130981,"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":0.9970999956130981,"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":0.983299970626831,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9815999865531921,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7343653440475464},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6642281413078308},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6486626267433167},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.559965968132019},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5596778392791748},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5506885051727295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5140032172203064},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5052919983863831},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5047930479049683},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4778996706008911},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4753030240535736},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4704788327217102},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.4676954746246338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36245912313461304},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.24757185578346252}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7343653440475464},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6642281413078308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6486626267433167},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.559965968132019},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5596778392791748},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5506885051727295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5140032172203064},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5052919983863831},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5047930479049683},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4778996706008911},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4753030240535736},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4704788327217102},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.4676954746246338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36245912313461304},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.24757185578346252},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8899029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2021597230","https://openalex.org/W2102593897","https://openalex.org/W2146086273","https://openalex.org/W2163352848","https://openalex.org/W2615751500","https://openalex.org/W2772533079","https://openalex.org/W2796645931"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3214791684","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2095903272","https://openalex.org/W2353265673"],"abstract_inverted_index":{"The":[0,62,178],"extraction":[1,22],"of":[2,20,39,69,113,155,170,180],"road":[3,21,28,49,66,71,75,115,149,176],"information":[4,31,154],"has":[5,32],"always":[6],"played":[7],"a":[8,48,166],"quite":[9],"important":[10],"role":[11],"in":[12],"civil":[13],"and":[14,57,101,150],"military.":[15],"With":[16],"the":[17,37,65,70,74,81,87,89,111,114,119,124,134,142,156,181,190],"gradual":[18],"maturity":[19],"technology,":[23],"how":[24],"to":[25,35,85,109,140],"automatically":[26],"extract":[27,110],"pavement":[29],"material":[30,50,143],"also":[33],"begun":[34],"attract":[36],"attention":[38],"researchers.":[40],"Aiming":[41],"at":[42],"this":[43,45],"problem,":[44],"paper":[46],"proposes":[47],"analysis":[51,122],"method":[52,63,159,191],"based":[53,72,174],"on":[54,73,175,184],"image":[55,163,173],"features":[56,112,164],"Support":[58],"Vector":[59],"Machine":[60],"(SVM).":[61],"extracts":[64],"surface":[67,116],"portion":[68],"binary":[76],"image.":[77],"Then":[78,131],"we":[79,132],"use":[80,133],"Rerinex":[82],"algorithm":[83],"[1]":[84],"denoise":[86],"image,":[88],"HSV":[90],"(Hue,":[91],"Saturation,":[92],"Value)":[93],"color":[94],"model,":[95],"Local":[96],"Binary":[97],"Patterns":[98],"texture":[99],"[2],":[100],"Gray":[102],"Level":[103],"Co-occurrence":[104],"Matrix":[105],"(GLCM)":[106],"are":[107],"used":[108],"pixels.":[117],"After":[118],"principal":[120],"component":[121],"reducing":[123],"dimension,":[125],"each":[126],"feature":[127],"vector":[128,136],"is":[129,165,192],"fused.":[130],"support":[135],"machine":[137],"(SVM)":[138],"classifier":[139],"analyze":[141],"(asphalt":[144],"concrete":[145,148],"road,":[146],"cement":[147],"bare":[151],"soil":[152],"road)":[153],"road.":[157],"This":[158],"that":[160,189],"combines":[161],"multiple":[162],"new":[167],"application":[168],"extension":[169],"remote":[171,185],"sensing":[172,186],"extraction.":[177],"results":[179],"classification":[182],"experiments":[183],"images":[187],"confirmed":[188],"effective.":[193]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}