{"id":"https://openalex.org/W4312726744","doi":"https://doi.org/10.1109/igarss46834.2022.9884572","title":"Spartina Alterniflora Classification at Patch Scale Based on Feature Fusion and Deep Learning","display_name":"Spartina Alterniflora Classification at Patch Scale Based on Feature Fusion and Deep Learning","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312726744","doi":"https://doi.org/10.1109/igarss46834.2022.9884572"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884572","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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/A5100438118","display_name":"Zhihui Wang","orcid":"https://orcid.org/0000-0002-4984-1623"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihui Wang","raw_affiliation_strings":["Geomatics College, Shandong University of Science and Technology,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Geomatics College, Shandong University of Science and Technology,Qingdao,China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101578655","display_name":"Yu Qu","orcid":"https://orcid.org/0000-0002-1400-6740"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Qu","raw_affiliation_strings":["Geomatics College, Shandong University of Science and Technology,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Geomatics College, Shandong University of Science and Technology,Qingdao,China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042581303","display_name":"Chunkai Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunkai Zheng","raw_affiliation_strings":["Geomatics College, Shandong University of Science and Technology,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Geomatics College, Shandong University of Science and Technology,Qingdao,China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100438118"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":0.7268,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71200672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":null,"first_page":"1540","last_page":"1543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.989300012588501,"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":0.989300012588501,"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/spartina-alterniflora","display_name":"Spartina alterniflora","score":0.8574953079223633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6486906409263611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5369119048118591},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5291880965232849},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4651449918746948},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4587865173816681},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3510622978210449},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.15878573060035706},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11961069703102112},{"id":"https://openalex.org/keywords/wetland","display_name":"Wetland","score":0.1059243381023407},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.08188602328300476},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.0635705292224884}],"concepts":[{"id":"https://openalex.org/C2779858377","wikidata":"https://www.wikidata.org/wiki/Q2697224","display_name":"Spartina alterniflora","level":4,"score":0.8574953079223633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6486906409263611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5369119048118591},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5291880965232849},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4651449918746948},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4587865173816681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3510622978210449},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.15878573060035706},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11961069703102112},{"id":"https://openalex.org/C67715294","wikidata":"https://www.wikidata.org/wiki/Q170321","display_name":"Wetland","level":2,"score":0.1059243381023407},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.08188602328300476},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0635705292224884},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C67268981","wikidata":"https://www.wikidata.org/wiki/Q30198","display_name":"Marsh","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884572","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1999517321","https://openalex.org/W2618046395","https://openalex.org/W2884436604","https://openalex.org/W3010665853","https://openalex.org/W3018528632"],"related_works":["https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W2144059113","https://openalex.org/W3003836766","https://openalex.org/W1964120219","https://openalex.org/W2136054869","https://openalex.org/W2000165426","https://openalex.org/W2546942002","https://openalex.org/W2016461833","https://openalex.org/W3197541072"],"abstract_inverted_index":{"Spartina":[0],"alterniflora":[1,36,89,108,139],"is":[2,58,62,192,198,201],"one":[3],"of":[4,34,51,87,106,137,143,172,184,217],"the":[5,32,42,48,55,103,110,123,144,153,180,185,195,204,213],"most":[6],"important":[7],"invasive":[8],"alien":[9],"plants":[10],"in":[11,14,109],"coastal":[12],"wetlands":[13],"China,":[15],"and":[16,60,72,116,150,161,194,208],"its":[17],"rapid":[18],"expansion":[19],"has":[20,209],"caused":[21],"serious":[22],"negative":[23],"ecological":[24],"impacts.":[25],"Current":[26],"researches":[27],"mainly":[28],"have":[29],"focused":[30],"on":[31,91,140],"monitoring":[33,49,82,86,216],"S.":[35,88,107,138,173,218],"using":[37,152],"moderate-resolution":[38],"satellite":[39,66],"images":[40,67],"at":[41,54],"regional":[43],"or":[44],"landscape":[45],"scale,":[46],"while":[47],"capability":[50],"early":[52],"invasion":[53],"patch":[56,214],"scale":[57,215],"limited,":[59],"it":[61],"difficult":[63],"to":[64,70],"obtain":[65],"stably":[68],"due":[69],"cloud":[71],"tidal":[73],"interference.":[74],"In":[75],"this":[76,127,190],"paper,":[77],"we":[78],"propose":[79],"a":[80,135],"semi-automatic":[81],"framework":[83],"for":[84,126,132,167,212],"patch-scale":[85],"based":[90],"deep":[92,156],"learning":[93,157],"techniques":[94],"with":[95,122],"unmanned":[96],"aerial":[97],"vehicle":[98],"(UAV)":[99],"RGB":[100],"images.":[101],"First,":[102],"spectral":[104],"characteristics":[105],"visible":[111],"light":[112],"band":[113],"were":[114,164],"analyzed,":[115],"Visible-band":[117],"Difference":[118],"Vegetation":[119],"Index":[120],"(VDVI)":[121],"strongest":[124],"stability":[125],"feature":[128],"type":[129],"was":[130,148],"selected":[131],"fusion.":[133],"Second,":[134],"dataset":[136],"both":[141],"sides":[142],"Yellow":[145],"River":[146],"estuary":[147],"constructed":[149],"trained":[151],"improved":[154],"U-Net++":[155],"network.":[158],"Finally,":[159],"prediction":[160,186],"accuracy":[162,182],"verification":[163],"carried":[165],"out":[166],"some":[168],"dense":[169],"distribution":[170],"areas":[171],"alterniflora.":[174,219],"The":[175],"experimental":[176],"results":[177,187],"show":[178],"that":[179],"overall":[181],"(OA)":[183],"obtained":[188],"by":[189],"method":[191],"98.1%,":[193],"kappa":[196],"coefficient":[197],"0.960,":[199],"which":[200],"better":[202],"than":[203],"traditional":[205],"classification":[206],"methods,":[207],"certain":[210],"significance":[211]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}