{"id":"https://openalex.org/W3106697608","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263586","title":"Comparisons of Different Seasonal Fused GF-1 Multispectral Images for Mapping Quasi-circular Vegetation Patches","display_name":"Comparisons of Different Seasonal Fused GF-1 Multispectral Images for Mapping Quasi-circular Vegetation Patches","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3106697608","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263586","mag":"3106697608"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei51763.2020.9263586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5045863929","display_name":"Qingsheng Liu","orcid":"https://orcid.org/0000-0001-5115-7567"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]},{"id":"https://openalex.org/I4391767971","display_name":"State Key Laboratory of Resources and Environmental Information System","ror":"https://ror.org/03w41by72","country_code":null,"type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793","https://openalex.org/I4391767971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingsheng Liu","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Geographic Sciences and Natural Resources Research,State Key Lab. of Resources and Environmental Information System,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Geographic Sciences and Natural Resources Research,State Key Lab. of Resources and Environmental Information System,Beijing,China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366","https://openalex.org/I4391767971"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5045863929"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210160793","https://openalex.org/I4391767971"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10800323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"311","last_page":"315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9975000023841858,"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":0.9975000023841858,"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":0.9912999868392944,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9890999794006348,"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/multispectral-image","display_name":"Multispectral image","score":0.8715096712112427},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.7341846823692322},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.526970386505127},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4409984052181244},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.4354564845561981},{"id":"https://openalex.org/keywords/seasonality","display_name":"Seasonality","score":0.4156070053577423},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3540728688240051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3346370458602905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.315233051776886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2661406099796295},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.24686706066131592},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.08493456244468689}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.8715096712112427},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.7341846823692322},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.526970386505127},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4409984052181244},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.4354564845561981},{"id":"https://openalex.org/C125403950","wikidata":"https://www.wikidata.org/wiki/Q2111082","display_name":"Seasonality","level":2,"score":0.4156070053577423},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3540728688240051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3346370458602905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.315233051776886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2661406099796295},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.24686706066131592},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08493456244468689},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei51763.2020.9263586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1125523343","https://openalex.org/W1194204893","https://openalex.org/W1969375100","https://openalex.org/W1975904229","https://openalex.org/W1989203457","https://openalex.org/W2082095955","https://openalex.org/W2088941391","https://openalex.org/W2100138660","https://openalex.org/W2182807969","https://openalex.org/W2290472085","https://openalex.org/W2332208325","https://openalex.org/W2415454320","https://openalex.org/W2515306179","https://openalex.org/W2515544675","https://openalex.org/W2588561483","https://openalex.org/W2770985577","https://openalex.org/W2789665835","https://openalex.org/W2805461187","https://openalex.org/W2806378263","https://openalex.org/W2884452734","https://openalex.org/W2888271200","https://openalex.org/W2891317683","https://openalex.org/W2896369314","https://openalex.org/W2917039524","https://openalex.org/W2944941447","https://openalex.org/W2960863152","https://openalex.org/W2967338577","https://openalex.org/W2989451156","https://openalex.org/W2998131875","https://openalex.org/W3014661830","https://openalex.org/W3015111510","https://openalex.org/W3043152991","https://openalex.org/W3082083081","https://openalex.org/W4248710273","https://openalex.org/W6685949391"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2124951708","https://openalex.org/W1544811710","https://openalex.org/W172072032","https://openalex.org/W2006066416","https://openalex.org/W3157073418","https://openalex.org/W2021642829","https://openalex.org/W2058127401"],"abstract_inverted_index":{"Mapping":[0],"the":[1,7,15,30,41,56,59,71,78,87,89,99,107,115,118,130,145,149,160,174,178,190,202,210,213,216,229,232,241],"quasi-circular":[2],"vegetation":[3,18,57,68,74],"patches":[4],"(QVPs)":[5],"is":[6,37],"most":[8],"basic":[9],"and":[10,24,27,70,75,122,205,227],"necessary":[11],"step":[12],"for":[13,54,97,128,239],"studying":[14],"mechanisms":[16],"of":[17,43,61,67,91,117,231],"pattern":[19],"formation,":[20],"spontaneous":[21],"plant":[22],"colonization,":[23],"ecosystem":[25],"maintenance":[26],"degradation":[28],"in":[29,212],"Yellow":[31],"River":[32],"Delta":[33],"(YRD),":[34],"China.":[35],"It":[36],"well":[38,104],"known":[39],"that":[40,156],"use":[42,60],"multi-seasonal":[44,92],"image":[45,65],"data":[46,162,192],"may":[47],"be":[48,223],"expected":[49],"to":[50,85,109,143,208,225],"obtain":[51],"better":[52],"results":[53,154],"mapping":[55,98,129,151,240],"than":[58,173],"a":[62],"single":[63],"date":[64],"because":[66],"phenology":[69],"contrasts":[72],"between":[73],"background.":[76],"Although":[77],"spring":[79,161,204],"GF-1":[80,94,125,236],"images":[81,96,127,207,238],"have":[82],"been":[83,103],"used":[84],"detect":[86],"QVPs,":[88],"potential":[90,116,230],"fused":[93,124,235],"multispectral":[95,126,237],"QVPs":[100,131,150,211],"has":[101],"not":[102],"explored.":[105],"With":[106],"objective":[108],"fill":[110],"this":[111],"gap,":[112],"we":[113],"evaluated":[114],"winter,":[119],"spring,":[120],"summer,":[121],"autumn":[123,191],"with":[132,137],"object-based":[133],"example-based":[134],"feature":[135],"extraction":[136],"support":[138],"vector":[139],"machine":[140,219],"classification":[141,157,175,185],"method":[142],"understand":[144],"seasonal":[146,181,234],"effect":[147],"on":[148,159,164,177,194],"accuracy.":[152],"The":[153,183],"showed":[155],"based":[158],"acquired":[163,193],"6":[165],"April":[166],"2014":[167],"(OA=99.8%,":[168],"kappa=0.988)":[169],"was":[170,187],"more":[171,218],"accurate":[172],"base":[176],"other":[179],"tree":[180],"images.":[182],"lowest":[184],"accuracy":[186],"obtained":[188],"from":[189],"September":[195],"21":[196],"2015":[197],"(OA=93.1%,":[198],"kappa=0.885).":[199],"We":[200],"recommend":[201],"he":[203],"winter":[206],"map":[209],"YRD.":[214],"In":[215],"future,":[217],"learning":[220],"techniques":[221],"should":[222],"applied":[224],"classify":[226],"compare":[228],"different":[233],"QVPs.":[242]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
