{"id":"https://openalex.org/W2979468187","doi":"https://doi.org/10.1109/multi-temp.2019.8866940","title":"Predicting surface reflectance using time series harmonic model and all available Landsat imagery","display_name":"Predicting surface reflectance using time series harmonic model and all available Landsat imagery","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2979468187","doi":"https://doi.org/10.1109/multi-temp.2019.8866940","mag":"2979468187"},"language":"en","primary_location":{"id":"doi:10.1109/multi-temp.2019.8866940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2019.8866940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","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/A5081960384","display_name":"Shuai Xie","orcid":"https://orcid.org/0000-0003-0298-0877"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Xie","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107865072","display_name":"Liangyun Liu","orcid":"https://orcid.org/0000-0002-7987-037X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangyun Liu","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014875315","display_name":"Xiao Zhang","orcid":"https://orcid.org/0000-0002-5026-8692"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Zhang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111159730","display_name":"Chen Xidong","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xidong Chen","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"64","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"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":0.9998000264167786,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.7927929162979126},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7176454067230225},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6371681690216064},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5529932975769043},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.43608561158180237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42355185747146606},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3482816219329834},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.34283125400543213},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.1420300006866455},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10890007019042969},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08915233612060547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.06648433208465576}],"concepts":[{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.7927929162979126},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7176454067230225},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6371681690216064},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5529932975769043},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.43608561158180237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42355185747146606},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3482816219329834},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.34283125400543213},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.1420300006866455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10890007019042969},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08915233612060547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.06648433208465576},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/multi-temp.2019.8866940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2019.8866940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","raw_type":"proceedings-article"},{"id":"mag:3192656313","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902249074975889","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1968563567","https://openalex.org/W2017657457","https://openalex.org/W2028240797","https://openalex.org/W2030864384","https://openalex.org/W2055718260","https://openalex.org/W2085282193","https://openalex.org/W2086620533","https://openalex.org/W2106584184","https://openalex.org/W2117059495","https://openalex.org/W2121690928","https://openalex.org/W2169394799","https://openalex.org/W2621021710","https://openalex.org/W2725897987","https://openalex.org/W2770221842","https://openalex.org/W6684758714"],"related_works":["https://openalex.org/W2356841320","https://openalex.org/W1919101720","https://openalex.org/W2121524756","https://openalex.org/W3128246805","https://openalex.org/W1998697009","https://openalex.org/W4390822878","https://openalex.org/W782553550","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"A":[0],"time":[1,40],"series":[2,41],"harmonic":[3],"(TSH)":[4],"model":[5,42,61,193,264],"for":[6,34,53,68,124,143,165,194,243,252,282],"predicting":[7,65],"surface":[8,66,130],"reflectance":[9,67],"using":[10],"all":[11],"available":[12,100],"Landsat":[13,87,105],"8":[14,88,106],"images":[15,107,178,277],"in":[16,90,113,180],"three":[17,225],"years":[18],"is":[19,32,62,265],"developed.":[20],"First,":[21],"a":[22,39],"cloud,":[23],"cloud":[24],"shadow,":[25],"and":[26,49,73,96,111,141,146,163,168,199,241,246,250,286],"snow":[27],"detection":[28],"algorithm":[29,82],"called":[30],"Fmask":[31],"used":[33,123,215],"eliminating":[35],"\u201cnoisy\u201d":[36],"observations.":[37],"Then,":[38],"that":[43,175,259,268],"has":[44],"components":[45],"of":[46,56,64,78,103,127,135,157,191,220,262,269,279],"overall,":[47],"seasonality":[48],"trend":[50],"are":[51,179,278],"estimated":[52],"each":[54,57],"pixel":[55],"spectral":[58],"band.":[59],"The":[60,81,132,150,172,207,256,273],"capable":[63],"pixels":[69],"at":[70],"any":[71,74],"location":[72],"date":[75],"assuming":[76],"persistence":[77],"land":[79],"cover.":[80],"was":[83,197,200,214],"applied":[84],"to":[85,216,267],"one":[86],"scene":[89],"North":[91],"China":[92],"(WRS":[93],"Path":[94],"123":[95],"Row":[97],"32).":[98],"All":[99],"(a":[101],"total":[102],"63)":[104],"acquired":[108],"between":[109],"2014":[110],"2016":[112],"Google":[114],"Earth":[115],"Engine":[116],"were":[117,122,138,160,238,247],"used.":[118],"Three":[119],"clearest":[120],"scenes":[121],"quality":[125],"assessment":[126],"the":[128,176,184,189,218,224,230],"predicted":[129,177],"reflectance.":[131],"average":[133,151,231],"R2":[134],"6":[136,158],"bands":[137,159],"0.75,":[139],"0.69":[140],"0.67":[142],"04/13/2014,":[144,166],"09/04/2014":[145,167],"10/06/2014":[147,169],"scene,":[148,170],"respectively.":[149,171],"Root":[152],"Mean":[153],"Square":[154],"Error":[155],"(RMSE)":[156],"0.025,":[161],"0.026":[162],"0.028":[164],"results":[173,257],"demonstrate":[174],"good":[181],"agreement":[182],"with":[183,202],"real":[185],"images.":[186],"In":[187],"addition,":[188],"performance":[190],"TSH":[192,244,263,274],"cloud-gap":[195,221],"fill":[196],"assessed":[198],"compared":[201],"Best-Available-Pixel":[203],"(BAP)":[204],"composite":[205,254,271],"method.":[206,255,272],"MODIS":[208],"Nadir":[209],"BRDF-Adjusted":[210],"Reflectance":[211],"product":[212],"(MCD43A4)":[213],"assess":[217],"error":[219],"fill.":[222],"For":[223],"selected":[226],"cloud-covered":[227],"test":[228],"regions,":[229],"R":[232],"<sup":[233],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[234],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[235],"/":[236],"RMSE":[237],"0.8/0.022,":[239],"0.63/0.014":[240],"0.8/0.018":[242],"model,":[245],"0.72/0.026,":[248],"0.53/0.016":[249],"0.66/0.032":[251],"BAP":[253,270],"conclude":[258],"prediction":[260],"accuracy":[261],"superior":[266],"model-derived":[275],"cloud-free":[276],"great":[280],"importance":[281],"multi-temporal":[283],"land-cover":[284],"classification":[285],"change":[287],"detection.":[288]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}