{"id":"https://openalex.org/W4387828929","doi":"https://doi.org/10.1109/igarss52108.2023.10282865","title":"Retrieval of Typhoon Wind Speed from Sentinel-1 Dual-Polarization SAR Based on Machine Learning","display_name":"Retrieval of Typhoon Wind Speed from Sentinel-1 Dual-Polarization SAR Based on Machine Learning","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387828929","doi":"https://doi.org/10.1109/igarss52108.2023.10282865"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 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/A5101484695","display_name":"Xintong Zhao","orcid":"https://orcid.org/0000-0001-7192-4639"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xintong Zhao","raw_affiliation_strings":["China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053849835","display_name":"Qiushuang Yan","orcid":"https://orcid.org/0000-0001-9185-3743"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiushuang Yan","raw_affiliation_strings":["China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072563820","display_name":"Chenqing Fan","orcid":"https://orcid.org/0000-0001-8719-3615"},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"funder","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210114556","display_name":"First Institute of Oceanography","ror":"https://ror.org/01y34t753","country_code":"CN","type":"facility","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210114556","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenqing Fan","raw_affiliation_strings":["Ministry of Natural Resources,First Institute of Oceanography,Qingdao,China,266061"],"affiliations":[{"raw_affiliation_string":"Ministry of Natural Resources,First Institute of Oceanography,Qingdao,China,266061","institution_ids":["https://openalex.org/I4210114556","https://openalex.org/I211433327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100436722","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0002-2635-7783"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"funder","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210114556","display_name":"First Institute of Oceanography","ror":"https://ror.org/01y34t753","country_code":"CN","type":"facility","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210114556","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580","First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum,College of Oceanography and Space Informatics,Qingdao,China,266580","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China","institution_ids":["https://openalex.org/I4210114556","https://openalex.org/I211433327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101484695"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":0.2816,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62442968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4068","last_page":"4071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11061","display_name":"Ocean Waves and Remote Sensing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11061","display_name":"Ocean Waves and Remote Sensing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.9994999766349792,"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/T10647","display_name":"Coastal and Marine Dynamics","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1904","display_name":"Earth-Surface Processes"},"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/typhoon","display_name":"Typhoon","score":0.8340766429901123},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8000248670578003},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.7586444020271301},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6796832084655762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6201180219650269},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5433526635169983},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5312041640281677},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5203304290771484},{"id":"https://openalex.org/keywords/tropical-cyclone","display_name":"Tropical cyclone","score":0.4915498197078705},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.47412919998168945},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.43720412254333496},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4226033091545105},{"id":"https://openalex.org/keywords/wind-direction","display_name":"Wind direction","score":0.4191136360168457},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39637482166290283},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.390440434217453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35457319021224976},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.30824047327041626},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.25258100032806396},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.184364914894104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14886274933815002},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13395142555236816}],"concepts":[{"id":"https://openalex.org/C181654704","wikidata":"https://www.wikidata.org/wiki/Q140588","display_name":"Typhoon","level":2,"score":0.8340766429901123},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8000248670578003},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.7586444020271301},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6796832084655762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6201180219650269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5433526635169983},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5312041640281677},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5203304290771484},{"id":"https://openalex.org/C29141058","wikidata":"https://www.wikidata.org/wiki/Q8092","display_name":"Tropical cyclone","level":2,"score":0.4915498197078705},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.47412919998168945},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.43720412254333496},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4226033091545105},{"id":"https://openalex.org/C107775477","wikidata":"https://www.wikidata.org/wiki/Q1057900","display_name":"Wind direction","level":3,"score":0.4191136360168457},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39637482166290283},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.390440434217453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35457319021224976},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.30824047327041626},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.25258100032806396},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.184364914894104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14886274933815002},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13395142555236816},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6000000238418579}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1977964797","https://openalex.org/W1993733000","https://openalex.org/W2054436772","https://openalex.org/W2060423551","https://openalex.org/W2121298821","https://openalex.org/W2293785379","https://openalex.org/W2746781231","https://openalex.org/W2805383893","https://openalex.org/W3024927067","https://openalex.org/W3129724029","https://openalex.org/W4220850976","https://openalex.org/W4229374174"],"related_works":["https://openalex.org/W2606526000","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655"],"abstract_inverted_index":{"The":[0,18,81,123,143],"200":[1],"dual-polarized":[2],"Sentinel-1":[3],"SAR":[4],"images":[5],"covering":[6],"typhoons":[7],"from":[8,78],"2018":[9],"to":[10],"2022":[11],"are":[12,21,66],"collocated":[13],"with":[14,103],"ERA5":[15],"reanalysis":[16],"data.":[17,80],"SAR-ERA5":[19],"collocations":[20],"randomly":[22],"divided":[23],"into":[24],"two":[25],"subsections:":[26],"one":[27],"for":[28,35,68],"model":[29,125,151],"training":[30,43],"(80%),":[31],"and":[32,60,111,121],"the":[33,41,50,56,61,69,85,95,100,104,136,150],"other":[34],"independent":[36],"testing":[37],"(20%).":[38],"Based":[39],"on":[40],"selected":[42],"samples,":[44],"three":[45,86],"machine":[46,87],"learning":[47,88],"models,":[48],"including":[49],"Back":[51],"Propagation":[52],"Neural":[53],"Networks":[54],"(BPNN),":[55],"Random":[57],"Forest":[58],"(RF),":[59],"Gaussian":[62],"Process":[63],"Regression":[64],"(GPR),":[65],"built":[67],"estimation":[70],"of":[71,138,146],"typhoon":[72],"sea":[73],"surface":[74],"wind":[75,133],"speed":[76],"(SSWS)":[77],"VV":[79],"results":[82],"show":[83],"that":[84],"models":[89],"achieve":[90],"significantly":[91],"better":[92,128],"performance":[93,102,137],"than":[94,129],"traditional":[96],"method.":[97],"BPNN":[98,130],"has":[99],"best":[101],"bias,":[105],"root":[106],"mean":[107],"square":[108],"error":[109],"(RMSE)":[110],"scattering":[112],"index":[113],"(SI)":[114],"respectively":[115],"being":[116],"-1.33":[117],"m/s,":[118],"3.25":[119],"m/s":[120],"1.5%.":[122],"GPR":[124],"performs":[126],"slightly":[127],"at":[131],"higher":[132],"speeds.":[134],"However,":[135],"RF":[139],"is":[140],"relatively":[141],"poor.":[142],"additional":[144],"introduction":[145],"VH":[147],"information":[148],"improves":[149],"performance.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}