{"id":"https://openalex.org/W3087852204","doi":"https://doi.org/10.3390/rs12183091","title":"Time-Series Model-Adjusted Percentile Features: Improved Percentile Features for Land-Cover Classification Based on Landsat Data","display_name":"Time-Series Model-Adjusted Percentile Features: Improved Percentile Features for Land-Cover Classification Based on Landsat Data","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3087852204","doi":"https://doi.org/10.3390/rs12183091","mag":"3087852204"},"language":"en","primary_location":{"id":"doi:10.3390/rs12183091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183091","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3091/pdf?version=1600826397","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/12/18/3091/pdf?version=1600826397","any_repository_has_fulltext":true},"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/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Xie","raw_affiliation_strings":["College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China","Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"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/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liangyun Liu","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113746922","display_name":"Jiangning Yang","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/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangning Yang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5107865072"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.9617,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.75694842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"18","first_page":"3091","last_page":"3091"},"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9957000017166138,"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/T10895","display_name":"Species Distribution and Climate Change","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/percentile","display_name":"Percentile","score":0.8399664163589478},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6981731057167053},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6284722089767456},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5916554927825928},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5336530804634094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42455852031707764},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4133809506893158},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.32477933168411255},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2631102502346039},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.25381457805633545},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1965644657611847},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1944155991077423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16762027144432068},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16308638453483582},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0984099805355072}],"concepts":[{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.8399664163589478},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6981731057167053},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6284722089767456},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5916554927825928},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5336530804634094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42455852031707764},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4133809506893158},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.32477933168411255},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2631102502346039},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.25381457805633545},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1965644657611847},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1944155991077423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16762027144432068},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16308638453483582},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0984099805355072},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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":3,"locations":[{"id":"doi:10.3390/rs12183091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183091","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3091/pdf?version=1600826397","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:867b80850ac64991b5dd7e11f0760c05","is_oa":true,"landing_page_url":"https://doaj.org/article/867b80850ac64991b5dd7e11f0760c05","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 12, Iss 18, p 3091 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/18/3091/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12183091","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 12; Issue 18; Pages: 3091","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12183091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12183091","pdf_url":"https://www.mdpi.com/2072-4292/12/18/3091/pdf?version=1600826397","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G1096709905","display_name":null,"funder_award_id":"ZDRW-ZS-2019-1","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3728277492","display_name":null,"funder_award_id":"41825002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4652898094","display_name":null,"funder_award_id":"XDA19090200","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G4761761132","display_name":null,"funder_award_id":"2017YFA0603001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6258415954","display_name":null,"funder_award_id":"Chinese","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320310017","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3087852204.pdf","grobid_xml":"https://content.openalex.org/works/W3087852204.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1889848888","https://openalex.org/W1963768209","https://openalex.org/W1966446776","https://openalex.org/W1982121855","https://openalex.org/W1983432010","https://openalex.org/W1993577784","https://openalex.org/W2017657457","https://openalex.org/W2024805021","https://openalex.org/W2025745000","https://openalex.org/W2028240797","https://openalex.org/W2030851497","https://openalex.org/W2030864384","https://openalex.org/W2042645898","https://openalex.org/W2047549267","https://openalex.org/W2055718260","https://openalex.org/W2056636001","https://openalex.org/W2060745228","https://openalex.org/W2061920292","https://openalex.org/W2074222846","https://openalex.org/W2078191571","https://openalex.org/W2078283574","https://openalex.org/W2081403294","https://openalex.org/W2097360283","https://openalex.org/W2130037317","https://openalex.org/W2132424470","https://openalex.org/W2135046866","https://openalex.org/W2138973222","https://openalex.org/W2140908571","https://openalex.org/W2151456308","https://openalex.org/W2164943663","https://openalex.org/W2167839896","https://openalex.org/W2176737848","https://openalex.org/W2181171301","https://openalex.org/W2199321793","https://openalex.org/W2261059368","https://openalex.org/W2540777836","https://openalex.org/W2553544826","https://openalex.org/W2584952387","https://openalex.org/W2605847660","https://openalex.org/W2619820913","https://openalex.org/W2621021710","https://openalex.org/W2725897987","https://openalex.org/W2911964244","https://openalex.org/W3008834779","https://openalex.org/W3098745759","https://openalex.org/W4294541781","https://openalex.org/W6687780495"],"related_works":["https://openalex.org/W1550559433","https://openalex.org/W2189235034","https://openalex.org/W2059841545","https://openalex.org/W2191239088","https://openalex.org/W2319948171","https://openalex.org/W2044237804","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W2119012848","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Percentile":[0],"features":[1],"derived":[2,113,158],"from":[3,32,114,159],"Landsat":[4,18,78,81,139,255],"time-series":[5,53,67,89,117,140,162],"data":[6,54,82,118,141,163,218],"are":[7,247],"widely":[8],"adopted":[9],"in":[10,52,225,260],"land-cover":[11,50,74,93,171],"classification.":[12],"However,":[13],"the":[14,29,38,66,92,99,115,122,155,160,170,175,188,216,222,237,261],"temporal":[15],"distribution":[16],"of":[17,142,232],"valid":[19,207],"observations":[20],"is":[21,55,71],"highly":[22],"uneven":[23],"across":[24],"different":[25,88],"pixels":[26,110],"due":[27],"to":[28,215],"gaps":[30],"resulting":[31],"clouds,":[33],"cloud":[34,265],"shadows,":[35],"snow,":[36],"and":[37,91,204,235],"scan":[39],"line":[40],"corrector":[41],"(SLC)-off":[42],"problem.":[43],"In":[44,59,209],"addition,":[45,210],"when":[46],"applying":[47],"percentile":[48,64,70],"features,":[49],"change":[51,101],"usually":[56],"not":[57],"considered.":[58],"this":[60,226],"paper,":[61],"an":[62],"improved":[63],"called":[65],"model":[68],"(TSM)-adjusted":[69],"proposed":[72,134,176,192,224],"for":[73,108,127,197,249],"classification":[75,147,239,253],"based":[76,241],"on":[77,138,242],"data.":[79],"The":[80,105,133,146,166,191,245],"were":[83,95,111,125,136,149],"first":[84],"modeled":[85],"using":[86,98,154,174,187,254],"three":[87,143],"models,":[90],"changes":[94],"continuously":[96],"monitored":[97],"continuous":[100],"detection":[102],"(CCD)":[103],"algorithm.":[104],"TSM-adjusted":[106,123,177],"percentiles":[107,124,157,178],"stable":[109],"then":[112],"synthetic":[116],"without":[119],"gaps.":[120,165],"Finally,":[121],"used":[126],"generating":[128],"supervised":[129],"random":[130],"forest":[131,198],"classifications.":[132],"methods":[135,223],"implemented":[137],"study":[144],"areas.":[145],"results":[148,167],"compared":[150],"with":[151,164,200,205,263],"those":[152,185],"obtained":[153,173,186],"original":[156,161,189],"show":[168],"that":[169],"classifications":[172],"have":[179],"significantly":[180],"higher":[181],"overall":[182,238],"accuracies":[183],"than":[184],"percentiles.":[190],"method":[193],"was":[194,212],"more":[195],"effective":[196],"types":[199],"obvious":[201],"phenological":[202],"characteristics":[203],"fewer":[206],"observations.":[208],"it":[211],"also":[213],"robust":[214],"training":[217],"sampling":[219],"strategy.":[220],"Overall,":[221],"work":[227],"can":[228],"provide":[229],"accurate":[230],"characterization":[231],"land":[233,251],"cover":[234,252],"improve":[236],"accuracy":[240],"such":[243],"metrics.":[244],"findings":[246],"promising":[248],"percentile-based":[250],"time":[256],"series":[257],"data,":[258],"especially":[259],"areas":[262],"frequent":[264],"coverage.":[266]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-10-01T00:00:00"}