{"id":"https://openalex.org/W2987133105","doi":"https://doi.org/10.1109/igarss.2019.8900617","title":"Garlic Mapping for Sentinel-2 Time-Series Data Using a Random Forest Classifier","display_name":"Garlic Mapping for Sentinel-2 Time-Series Data Using a Random Forest Classifier","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2987133105","doi":"https://doi.org/10.1109/igarss.2019.8900617","mag":"2987133105"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8900617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900617","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":"conference-paper","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/A5044566745","display_name":"Zhaoyang Chai","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Chai","raw_affiliation_strings":["The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385569","display_name":"Hongyan Zhang","orcid":"https://orcid.org/0000-0001-6424-3261"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Zhang","raw_affiliation_strings":["The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102953701","display_name":"Xiong Xu","orcid":"https://orcid.org/0000-0003-3510-4160"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Xu","raw_affiliation_strings":["College of Surveying and Geo-informatics, Tongji University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-informatics, Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100673818","display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, P.R. China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"83","issue":null,"first_page":"7224","last_page":"7227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.996999979019165,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9824000000953674,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.96670001745224,"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/random-forest","display_name":"Random forest","score":0.7934317588806152},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6000986099243164},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5882138609886169},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5869517922401428},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48072341084480286},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.407749742269516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4046069383621216},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39740777015686035},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3417086601257324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33077365159988403},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1390657126903534},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10463792085647583}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7934317588806152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000986099243164},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5882138609886169},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5869517922401428},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48072341084480286},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.407749742269516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4046069383621216},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39740777015686035},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3417086601257324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33077365159988403},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1390657126903534},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10463792085647583},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8900617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900617","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":0.6800000071525574,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1976129996","https://openalex.org/W1991861340","https://openalex.org/W2024805021","https://openalex.org/W2060304003","https://openalex.org/W2085992718","https://openalex.org/W2113410727","https://openalex.org/W2133941557","https://openalex.org/W2557992764","https://openalex.org/W2592712793","https://openalex.org/W2737836416","https://openalex.org/W2767953525","https://openalex.org/W2911964244","https://openalex.org/W3006106690","https://openalex.org/W6741667914","https://openalex.org/W6746291272","https://openalex.org/W6821000344"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W1924178503","https://openalex.org/W2889302474","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Crop":[0],"classification":[1],"and":[2,10,13,29,47,125],"mapping":[3,78],"are":[4],"important":[5,25],"to":[6,66],"socioeconomic,":[7],"food":[8],"safety,":[9],"policy-making.":[11],"Accurate":[12],"timely":[14],"spatial":[15],"distribution":[16],"of":[17,70,76,123,129],"crop":[18],"types":[19],"based":[20,79],"on":[21,38,80],"remote":[22],"sensing":[23],"is":[24,55,84],"for":[26],"both":[27],"scientific":[28],"practical":[30],"purposes.":[31],"However,":[32],"the":[33,51,68,101,109],"existing":[34],"studies":[35],"mostly":[36],"focused":[37],"main":[39],"crops,":[40],"such":[41],"as":[42,100],"winter":[43],"wheat,":[44],"paddy":[45],"rice":[46],"some":[48],"others.":[49],"For":[50],"garlic":[52,71,77],"crop,":[53],"there":[54],"few":[56],"relevant":[57],"research":[58],"available.":[59],"So":[60],"in":[61,64],"this":[62],"paper,":[63],"order":[65],"explore":[67],"feasibility":[69],"extraction,":[72],"a":[73,115,126],"preliminary":[74],"experiment":[75],"random":[81],"forest":[82],"(GMRF)":[83],"carried":[85],"out":[86],"with":[87,118],"multi-temporal":[88],"10-m":[89],"resolution":[90],"Sentinel-2":[91],"images,":[92],"by":[93],"taking":[94],"Jinxiang":[95],"County,":[96],"Shandong":[97],"Province,":[98],"China":[99],"experimental":[102,105],"area.":[103],"The":[104],"results":[106],"suggest":[107],"that":[108],"proposed":[110],"GMRF":[111],"method":[112],"can":[113],"achieve":[114],"good":[116],"performance,":[117],"an":[119],"overall":[120],"accuracy":[121],"(OA)":[122],"98.56%":[124],"kappa":[127],"coefficient":[128],"0.967.":[130]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}