{"id":"https://openalex.org/W4206765829","doi":"https://doi.org/10.1109/tgrs.2021.3140144","title":"Multitask Deep Learning Framework for Spatiotemporal Fusion of NDVI","display_name":"Multitask Deep Learning Framework for Spatiotemporal Fusion of NDVI","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4206765829","doi":"https://doi.org/10.1109/tgrs.2021.3140144"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3140144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3140144","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5003240149","display_name":"Duo Jia","orcid":"https://orcid.org/0000-0002-0238-1930"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duo Jia","raw_affiliation_strings":["Faculty of Geographical Science, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0238-1930","affiliations":[{"raw_affiliation_string":"Faculty of Geographical Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031780513","display_name":"Changxiu Cheng","orcid":"https://orcid.org/0000-0003-2988-8915"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4391768099","display_name":"State Key Laboratory of Earth Surface Processes and Resource Ecology","ror":"https://ror.org/050mxte83","country_code":null,"type":"facility","lineage":["https://openalex.org/I25254941","https://openalex.org/I4391768099"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changxiu Cheng","raw_affiliation_strings":["State Key Laboratory of Earth Surface Processes and Resource Ecology, the Key Laboratory of Environmental Change and Natural Disaster, and the Center for Geodata and Analysis, Beijing Normal University, Beijing, China","National Tibetan Plateau Data Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Earth Surface Processes and Resource Ecology, the Key Laboratory of Environmental Change and Natural Disaster, and the Center for Geodata and Analysis, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4391768099"]},{"raw_affiliation_string":"National Tibetan Plateau Data Center, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110705119","display_name":"Shi Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Shen","raw_affiliation_strings":["Center for Geodata and Analysis, Beijing Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9126-229X","affiliations":[{"raw_affiliation_string":"Center for Geodata and Analysis, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015987586","display_name":"Lixin Ning","orcid":"https://orcid.org/0000-0002-1483-9849"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Ning","raw_affiliation_strings":["Faculty of Geographical Science, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Geographical Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0854,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9390095,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9937000274658203,"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/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.6583089828491211},{"id":"https://openalex.org/keywords/moderate-resolution-imaging-spectroradiometer","display_name":"Moderate-resolution imaging spectroradiometer","score":0.6399518251419067},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6322715282440186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.631624698638916},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6265812516212463},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.602998673915863},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5630851984024048},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5145927667617798},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5114821195602417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49130454659461975},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4418870210647583},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.4310103952884674},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4128059148788452},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32910317182540894},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22519272565841675},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21879896521568298},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.20355597138404846},{"id":"https://openalex.org/keywords/climate-change","display_name":"Climate change","score":0.1108812689781189},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08538785576820374}],"concepts":[{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.6583089828491211},{"id":"https://openalex.org/C2777007095","wikidata":"https://www.wikidata.org/wiki/Q676840","display_name":"Moderate-resolution imaging spectroradiometer","level":3,"score":0.6399518251419067},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6322715282440186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.631624698638916},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6265812516212463},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.602998673915863},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5630851984024048},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5145927667617798},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5114821195602417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49130454659461975},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4418870210647583},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.4310103952884674},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4128059148788452},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32910317182540894},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22519272565841675},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21879896521568298},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.20355597138404846},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.1108812689781189},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08538785576820374},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3140144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3140144","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"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":44,"referenced_works":["https://openalex.org/W1970515153","https://openalex.org/W1982121855","https://openalex.org/W2001559050","https://openalex.org/W2002908628","https://openalex.org/W2018636632","https://openalex.org/W2031596845","https://openalex.org/W2056811372","https://openalex.org/W2069276699","https://openalex.org/W2088603520","https://openalex.org/W2096885759","https://openalex.org/W2113410727","https://openalex.org/W2113503197","https://openalex.org/W2117971662","https://openalex.org/W2124073857","https://openalex.org/W2133665775","https://openalex.org/W2138751033","https://openalex.org/W2151011640","https://openalex.org/W2159269332","https://openalex.org/W2200350976","https://openalex.org/W2552447511","https://openalex.org/W2573859572","https://openalex.org/W2584130088","https://openalex.org/W2767886251","https://openalex.org/W2793445582","https://openalex.org/W2795018073","https://openalex.org/W2843468165","https://openalex.org/W2866634454","https://openalex.org/W2895598217","https://openalex.org/W2897285410","https://openalex.org/W2904952058","https://openalex.org/W2938854198","https://openalex.org/W2939570633","https://openalex.org/W2989531848","https://openalex.org/W2992343265","https://openalex.org/W2999347784","https://openalex.org/W3007850788","https://openalex.org/W3034422010","https://openalex.org/W3037983056","https://openalex.org/W3047166575","https://openalex.org/W3096444413","https://openalex.org/W3102533665","https://openalex.org/W3132908999","https://openalex.org/W6618476874","https://openalex.org/W6775935551"],"related_works":["https://openalex.org/W3207046288","https://openalex.org/W3023446922","https://openalex.org/W4324030030","https://openalex.org/W4385533602","https://openalex.org/W3189212133","https://openalex.org/W4382239404","https://openalex.org/W4382519838","https://openalex.org/W3183766399","https://openalex.org/W2736619525","https://openalex.org/W2725495055"],"abstract_inverted_index":{"High":[0],"spatial":[1,53,70],"and":[2,62,122,190,198],"temporal":[3,56,67],"resolution":[4],"normalized":[5],"difference":[6],"vegetation":[7],"index":[8],"(NDVI)":[9],"time":[10,98,164],"series":[11],"are":[12,114,214],"indispensable":[13],"for":[14,34,143,160],"monitoring":[15],"land":[16],"surfaces":[17],"dynamics":[18],"in":[19,96,116,151,176],"spatiotemporally":[20],"heterogeneous":[21],"areas.":[22],"Spatiotemporal":[23],"fusion":[24,111,132,145,200,219],"(STF)":[25],"is":[26,86,223],"one":[27,44],"of":[28,43,48,162,170,186,202],"the":[29,41,83,91,97,101,144,184,187,191,227],"most":[30],"common":[31],"methods":[32,39,107,137],"used":[33,231],"producing":[35],"such":[36,58,72],"data.":[37],"These":[38],"require":[40],"use":[42],"or":[45],"two":[46,168,177],"pairs":[47,209],"fine":[49,52,66,94],"images":[50,64],"(with":[51],"but":[54,68,113],"rough":[55,69],"resolution,":[57,71],"as":[59,73,232],"Landsat":[60],"images)":[61],"coarse":[63,80],"[with":[65],"Moderate":[74],"Resolution":[75],"Imaging":[76],"Spectroradiometer":[77],"(MODIS)].":[78],"A":[79],"image":[81,95,208],"at":[82,211],"prediction":[84],"date":[85],"also":[87,128],"required":[88],"to":[89,182,229],"predict":[90],"corresponding":[92],"missing":[93],"series.":[99],"Recently,":[100],"proposed":[102,188],"deep":[103],"learning":[104],"(DL)-based":[105],"STF":[106,136,161,172],"have":[108],"achieved":[109],"promising":[110],"performance":[112],"challenged":[115],"areas":[117],"with":[118],"frequent":[119],"cloud":[120],"contamination":[121],"landcover":[123,204],"change":[124],"prediction,":[125],"while":[126],"they":[127],"suffer":[129],"from":[130],"unstable":[131],"performance.":[133],"Moreover,":[134],"current":[135],"lack":[138],"a":[139,156,218,233],"quality":[140,234],"assessment":[141,235],"process":[142],"results.":[146],"To":[147],"address":[148],"these":[149],"limitations,":[150],"this":[152],"article,":[153],"we":[154],"propose":[155],"multitask":[157],"DL":[158],"framework":[159],"NDVI":[163],"series,":[165],"which":[166,225],"integrates":[167],"types":[169],"DL-based":[171],"methods.":[173],"Four":[174],"experiments":[175],"study":[178],"sites":[179],"were":[180],"conducted":[181],"test":[183],"effectiveness":[185],"method,":[189],"results":[192],"indicate":[193],"that":[194],"it":[195],"achieves":[196],"accurate":[197],"stable":[199],"capable":[201],"predicting":[203],"changes":[205],"even":[206],"when":[207],"obtained":[210],"long":[212],"intervals":[213],"used.":[215],"In":[216],"addition,":[217],"uncertainty":[220],"estimation":[221],"method":[222],"proposed,":[224],"has":[226],"potential":[228],"be":[230],"metric.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}