{"id":"https://openalex.org/W2988102477","doi":"https://doi.org/10.1109/igarss.2019.8900340","title":"Fill Invalid Pixels of Thematic Map Using Composited IMAGE","display_name":"Fill Invalid Pixels of Thematic Map Using Composited IMAGE","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2988102477","doi":"https://doi.org/10.1109/igarss.2019.8900340","mag":"2988102477"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8900340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900340","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/A5008417937","display_name":"Yong Pang","orcid":"https://orcid.org/0000-0002-9760-6580"},"institutions":[{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pang Yong","raw_affiliation_strings":["Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088404682","display_name":"Zengyuan Li","orcid":"https://orcid.org/0000-0001-9746-938X"},"institutions":[{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zengyuan","raw_affiliation_strings":["Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101065097","display_name":"Fan Shunxiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Shunxiang","raw_affiliation_strings":["Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]}]},{"author_position":"last","author":{"id":null,"display_name":"Meng Shili","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114891","display_name":"Institute of Forest Resource Information Techniques","ror":"https://ror.org/01h5d6x15","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114891","https://openalex.org/I4210128615","https://openalex.org/I4210134523"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Shili","raw_affiliation_strings":["Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China","institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5008417937"],"corresponding_institution_ids":["https://openalex.org/I4210114891","https://openalex.org/I4210128615"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11699045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"6748","last_page":"6751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9997000098228455,"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":0.9997000098228455,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9987000226974487,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9979000091552734,"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/thematic-map","display_name":"Thematic map","score":0.9014256000518799},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7735920548439026},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.719552755355835},{"id":"https://openalex.org/keywords/shadow","display_name":"Shadow (psychology)","score":0.7108710408210754},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6730070114135742},{"id":"https://openalex.org/keywords/cloud-cover","display_name":"Cloud cover","score":0.539581298828125},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5094974637031555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4891064763069153},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4699426293373108},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4698340594768524},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.44618645310401917},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.24083545804023743},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.23737439513206482},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05215775966644287}],"concepts":[{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.9014256000518799},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7735920548439026},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.719552755355835},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.7108710408210754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6730070114135742},{"id":"https://openalex.org/C206887242","wikidata":"https://www.wikidata.org/wiki/Q830457","display_name":"Cloud cover","level":3,"score":0.539581298828125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5094974637031555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4891064763069153},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4699426293373108},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4698340594768524},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.44618645310401917},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.24083545804023743},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.23737439513206482},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05215775966644287},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8900340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8900340","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":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1754365911","https://openalex.org/W2063352907","https://openalex.org/W2106584184","https://openalex.org/W2392589925"],"related_works":["https://openalex.org/W2291311298","https://openalex.org/W2378021067","https://openalex.org/W2347703439","https://openalex.org/W2371027582","https://openalex.org/W2076654158","https://openalex.org/W4244478748","https://openalex.org/W2362328851","https://openalex.org/W2366119473","https://openalex.org/W4223488648","https://openalex.org/W2372311246"],"abstract_inverted_index":{"Due":[0],"to":[1,13,50,96,107,143],"the":[2,30,59,68,75,82,86,98,109,113,130],"cloud":[3,38,40],"coverage":[4],"in":[5,29,58,67,112,122,126],"optical":[6],"remote":[7],"sensing":[8],"data,":[9],"it":[10,138],"is":[11,65,94,105,118,139],"challenging":[12],"have":[14],"a":[15,45,145],"cloud-free":[16,52,146],"image":[17,47],"over":[18],"large":[19],"region.":[20],"These":[21],"inevitable":[22],"cloud/cloud":[23],"shadow":[24,41],"pixels":[25],"bring":[26],"invalid":[27,56,87,110],"patches":[28],"derived":[31],"thematic":[32,60,69,83,114],"maps,":[33],"which":[34],"usually":[35],"labeled":[36],"as":[37],"and":[39,71,120,153],"types.":[42],"We":[43],"use":[44],"pixel-level":[46],"composition":[48],"method":[49,93,117],"generate":[51],"image.":[53,73,100],"For":[54],"each":[55],"patch":[57,111],"map,":[61],"an":[62,140],"enlarged":[63],"area":[64],"extracted":[66],"map":[70,84,125,149],"composited":[72,99],"Then":[74],"training":[76],"data":[77],"are":[78],"generated":[79],"automatically":[80],"using":[81],"surrounded":[85],"patch.":[88],"The":[89,101,135],"Random":[90],"Forest":[91],"(RF)":[92],"used":[95,106],"classify":[97],"new":[102],"classification":[103],"result":[104,136],"fill":[108],"map.":[115],"This":[116],"tested":[119],"evaluated":[121],"forest":[123,147],"cover":[124,148],"selected":[127],"sites":[128],"of":[129],"Greater":[131],"Mekong":[132],"Subregion":[133],"(GMS).":[134],"shows":[137],"efficient":[141],"way":[142],"produce":[144],"for":[150],"further":[151],"analysis":[152],"applications.":[154]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}