{"id":"https://openalex.org/W7104381733","doi":"https://doi.org/10.5281/zenodo.15678251","title":"HLS-GPT trained model and training data","display_name":"HLS-GPT trained model and training data","publication_year":2025,"publication_date":"2025-06-16","ids":{"openalex":"https://openalex.org/W7104381733","doi":"https://doi.org/10.5281/zenodo.15678251"},"language":null,"primary_location":{"id":"doi:10.5281/zenodo.15678251","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.15678251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.15678251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhang, Hankui","orcid":"https://orcid.org/0000-0003-4470-3616"},"institutions":[{"id":"https://openalex.org/I177156846","display_name":"South Dakota State University","ror":"https://ror.org/015jmes13","country_code":"US","type":"education","lineage":["https://openalex.org/I177156846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhang, Hankui","raw_affiliation_strings":["South Dakota State University"],"raw_orcid":"https://orcid.org/0000-0003-4470-3616","affiliations":[{"raw_affiliation_string":"South Dakota State University","institution_ids":["https://openalex.org/I177156846"]}]},{"author_position":"last","author":{"id":null,"display_name":"Junjie, Li","orcid":"https://orcid.org/0009-0008-3740-8452"},"institutions":[{"id":"https://openalex.org/I177156846","display_name":"South Dakota State University","ror":"https://ror.org/015jmes13","country_code":"US","type":"education","lineage":["https://openalex.org/I177156846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junjie, Li","raw_affiliation_strings":["South Dakota State University"],"raw_orcid":"https://orcid.org/0009-0008-3740-8452","affiliations":[{"raw_affiliation_string":"South Dakota State University","institution_ids":["https://openalex.org/I177156846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177156846"],"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":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6277999877929688},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5175999999046326},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5069000124931335},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.49779999256134033},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4546000063419342},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3779999911785126},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.36149999499320984}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6277999877929688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5443999767303467},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.49779999256134033},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4546000063419342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38449999690055847},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3779999911785126},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.36070001125335693},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2953000068664551},{"id":"https://openalex.org/C3020136221","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time sequence","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28630000352859497},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C2983696493","wikidata":"https://www.wikidata.org/wiki/Q7705730","display_name":"Test site","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.15678251","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.15678251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.15678251","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.15678251","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,298,419],"collection":[1],"contains":[2],"the":[3,8,15,31,69,72,139,151,177,190,193,202,215,276,287,369,389,402,405,464,468,474],"trained":[4],"model":[5,65,73,406],"(.h5)":[6],"and":[7,10,38,54,112,122,169,265,278,332,359,379,437],"training":[9,117,145,180,436],"test":[11,123,182],"data":[12,135,413],"(.npy)":[13],"for":[14,21,50,67,233,240,247,254,262,270,292,404,430],"HLS-GPT":[16],"annual":[17],"time":[18,95,195,231,238,245,252,260,268,280,395],"series":[19,96,196,281,308],"reconstruction":[20],"Conterminous":[22],"United":[23],"States":[24],"(CONUS).":[25],"More":[26],"details":[27],"can":[28],"refer":[29,75,478],"to":[30,76,323,425,473,479],"paper:":[32],"Li,":[33],"J.,":[34],"Zhang,":[35],"H.":[36],"K.,":[37],"Roy,":[39],"D.":[40],"P.":[41],"(2025).":[42],"HLS-GPT:":[43],"A":[44],"Generative":[45],"Pretrained":[46],"Transformer":[47,295],"(GPT)":[48],"Model":[49],"Accurate":[51],"Harmonized":[52],"Landsat":[53,203,230,244,259,277,367],"Sentinel-2":[55,141,216,237,251,267,279],"(HLS)":[56],"Reflectance":[57],"Time":[58,307],"Series":[59],"Reconstruction.":[60],"In":[61,128,387],"review.":[62],"1.best_model_GAPS_P0.5_versionv7_27.h5":[63],"Trained":[64],"weights":[66],"HLS-GPT,":[68],"structure":[70],"of":[71,179,192,208,221,329],"please":[74,477],"Li":[77],"et":[78],"al.,":[79],"2025.":[80],"2.AlignedCONUS_v1_6_training_test_data.zip":[81],"We":[82],"collected":[83],"11-year":[84,194],"(2013-2023)":[85],"good-quality":[86],"(not":[87],"cloud,":[88],"cloud":[89],"shadow":[90],"or":[91,146,181,466],"ice/snow)":[92],"HLS":[93,105,152],"reflectance":[94,336],"from":[97,136,411,448],"312,950":[98],"pixel":[99,183],"locations":[100],"evenly":[101],"distributed":[102],"across":[103,110],"96":[104],"tiles":[106],"(every":[107],"other":[108],"tile":[109],"CONUS)":[111],"randomly":[113],"split":[114],"them":[115],"into":[116],"(80%,":[118],"250,360":[119],"pixels":[120,459],")":[121],"(20%,":[124],"62,590":[125],"pixels)":[126],"locations.":[127,184],"our":[129,449],"paper,":[130],"we":[131],"only":[132,301],"used":[133,400],"9-year":[134],"2015":[137],"since":[138],"first":[140,173,199],"satellite":[142],"launch.":[143],"The":[144,172,185,198,211,224,318,335,377,435],"testing":[147,412,438],"input":[148],"x":[149],"(i.e.,":[150],"reflectance)":[153],"is":[154,226,290,383,420,446],"stored":[155],"as":[156,227,340],"a":[157,206,219],"3D":[158],"matrix":[159],"with":[160,205,218,309,316,375,415],"dimensions":[161],"n":[162],"\u00d7":[163],"(":[164],"(176+176)\u00d711)":[165],"\u00d713":[166],"in":[167,286,385,401,421,463],"AlignedCONUS_v1_6_multi_year_train.npy":[168],"AlignedCONUS_v1_6_multi_year_test.npy,":[170],"respectively,":[171],"dimension,":[174,187,320],"n,":[175],"represents":[176,189,201,214],"number":[178],"second":[186,212],"(176+176)\u00d711,":[188],"length":[191],"(2013-2023):":[197],"176":[200,209,213,222,229,236,243,250,258,266,312],"data,":[204,217,368,476],"maximum":[207,220],"dates.":[210,223,418],"sequence":[225],"follows:":[228,341],"points":[232,239,246,253,261,269],"year":[234,241,248,255,263,271,330,394],"2013,":[235,242],"2014,":[249,256],"\u2026,":[257],"2023,":[264],"2023.":[272],"For":[273,366,470],"each":[274],"record,":[275],"are":[282,338,373,461],"temporally":[283],"aligned\u2014identical":[284],"dates":[285],"same":[288],"order\u2014which":[289],"essential":[291],"concatenating":[293],"sensor-specific":[294],"feature":[296],"vectors.":[297],"alignment":[299],"introduces":[300],"minimal":[302],"computational":[303],"overhead":[304],"at":[305],"inference.":[306],"fewer":[310],"than":[311],"observations":[313],"were":[314,440],"padded":[315],"-9999.":[317,376],"third":[319],"13,":[321],"corresponds":[322],"spectral":[324],"information,":[325],"including":[326],"year,":[327],"day":[328],"(DOY),":[331],"normalized":[333],"reflectance.":[334],"bands":[337,356,372],"ordered":[339],"four":[342,371],"visible":[343],"bands,":[344,353],"one":[345,360,393],"near-infrared":[346],"(NIR)":[347],"band,":[348],"two":[349],"shortwave":[350],"infrared":[351],"(SWIR)":[352],"three":[354],"red-edge":[355],"(Sentinel-2":[357,364],"only),":[358],"broad":[361],"NIR":[362],"band":[363],"only).":[365],"last":[370],"filled":[374],"mean":[378],"std":[380],"normlization":[381],"file":[382],"included":[384],"https://github.com/junjieliwhu/HLSGPT.":[386],"addition,":[388],"AlignedCONUS_v1_6_random_selected_one_year_test.npy":[390],"stores":[391],"4,157,97":[392],"sereis":[396],"(4,157,97\u00d7":[397],"(176+176)":[398],"\u00d713)":[399],"paper":[403],"evaluation":[407],"that":[408,454,460],"was":[409],"extracted":[410],"AlignedCONUS_v1_6_multi_year_test.npy":[414],"random":[416],"starting":[417],"case":[422],"users":[423],"want":[424],"develop":[426],"more":[427],"advanced":[428],"models":[429],"comparison":[431],"purpose.":[432],"3.":[433],"AlignedCONUS_scale60_all_tiles_v1_6_filtered.parquet":[434,445],"files":[439],"generated":[441],"by":[442],"processing":[443],"AlignedCONUS_scale60_all_tiles_v1_6_filtered.parquet.":[444],"derived":[447],"previous":[450],"work":[451],"(https://zenodo.org/records/14715402),":[452],"except":[453],"this":[455],"dataset":[456],"filters":[457],"out":[458],"located":[462],"ocean":[465],"outside":[467],"CONUS.":[469],"an":[471],"introduction":[472],"original":[475],"https://zenodo.org/records/14715402":[480]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-08T00:00:00"}