{"id":"https://openalex.org/W3206756933","doi":"https://doi.org/10.1109/igarss47720.2021.9554371","title":"Hindcast of Soil Moisture Using SMAP, Land Surface Model Output Data, and Regression Methods","display_name":"Hindcast of Soil Moisture Using SMAP, Land Surface Model Output Data, and Regression Methods","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3206756933","doi":"https://doi.org/10.1109/igarss47720.2021.9554371","mag":"3206756933"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9554371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5061659921","display_name":"Maciel Zortea","orcid":"https://orcid.org/0000-0002-9758-5273"},"institutions":[{"id":"https://openalex.org/I4210113516","display_name":"IBM Research - Brazil","ror":"https://ror.org/01fxqdx25","country_code":"BR","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210113516","https://openalex.org/I4210114115"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Maciel Zortea","raw_affiliation_strings":["IBM Research,Rio de Janeiro,Brazil"],"affiliations":[{"raw_affiliation_string":"IBM Research,Rio de Janeiro,Brazil","institution_ids":["https://openalex.org/I4210113516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090234747","display_name":"Miguel Paredes","orcid":"https://orcid.org/0000-0003-2726-3049"},"institutions":[{"id":"https://openalex.org/I4210113516","display_name":"IBM Research - Brazil","ror":"https://ror.org/01fxqdx25","country_code":"BR","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210113516","https://openalex.org/I4210114115"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Miguel Paredes","raw_affiliation_strings":["IBM Research,Rio de Janeiro,Brazil"],"affiliations":[{"raw_affiliation_string":"IBM Research,Rio de Janeiro,Brazil","institution_ids":["https://openalex.org/I4210113516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030173480","display_name":"L. S. A. Martins","orcid":"https://orcid.org/0000-0003-3631-8056"},"institutions":[{"id":"https://openalex.org/I4210113516","display_name":"IBM Research - Brazil","ror":"https://ror.org/01fxqdx25","country_code":"BR","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210113516","https://openalex.org/I4210114115"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leonardo S. A. Martins","raw_affiliation_strings":["IBM Research,Rio de Janeiro,Brazil"],"affiliations":[{"raw_affiliation_string":"IBM Research,Rio de Janeiro,Brazil","institution_ids":["https://openalex.org/I4210113516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061659921"],"corresponding_institution_ids":["https://openalex.org/I4210113516"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11219217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6100","last_page":"6103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":1.0,"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/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9975000023841858,"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"}},{"id":"https://openalex.org/T10716","display_name":"Soil and Unsaturated Flow","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/data-assimilation","display_name":"Data assimilation","score":0.8398089408874512},{"id":"https://openalex.org/keywords/hindcast","display_name":"Hindcast","score":0.736322283744812},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.6792250275611877},{"id":"https://openalex.org/keywords/water-content","display_name":"Water content","score":0.5847058892250061},{"id":"https://openalex.org/keywords/radiometer","display_name":"Radiometer","score":0.5407926440238953},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5150175094604492},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.49805235862731934},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4920796751976013},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.4821067154407501},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3991454243659973},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.3228955864906311},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23227936029434204},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1888449490070343},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12003657221794128},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09517708420753479},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07075268030166626}],"concepts":[{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.8398089408874512},{"id":"https://openalex.org/C83002819","wikidata":"https://www.wikidata.org/wiki/Q798528","display_name":"Hindcast","level":2,"score":0.736322283744812},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.6792250275611877},{"id":"https://openalex.org/C24939127","wikidata":"https://www.wikidata.org/wiki/Q373499","display_name":"Water content","level":2,"score":0.5847058892250061},{"id":"https://openalex.org/C120189094","wikidata":"https://www.wikidata.org/wiki/Q850281","display_name":"Radiometer","level":2,"score":0.5407926440238953},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5150175094604492},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.49805235862731934},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4920796751976013},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.4821067154407501},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3991454243659973},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.3228955864906311},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23227936029434204},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1888449490070343},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12003657221794128},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09517708420753479},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07075268030166626},{"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/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9554371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2738911869","https://openalex.org/W2805415962","https://openalex.org/W2896500956","https://openalex.org/W2916889011","https://openalex.org/W3096353891","https://openalex.org/W3125807057","https://openalex.org/W4205166093"],"related_works":["https://openalex.org/W2332912399","https://openalex.org/W2895732286","https://openalex.org/W2537396124","https://openalex.org/W4220967543","https://openalex.org/W335333222","https://openalex.org/W4236597287","https://openalex.org/W2636138124","https://openalex.org/W3111891220","https://openalex.org/W4242324119","https://openalex.org/W2161050690"],"abstract_inverted_index":{"This":[0],"work":[1],"addresses":[2],"the":[3,40,53,73,77,86,106,109,149],"problem":[4],"of":[5,29,108,115],"artificially":[6],"extending":[7],"satellite-derived":[8],"soil":[9,13,35,49,79,87],"moisture":[10,14,36,50,88],"data":[11],"using":[12],"estimates":[15,37],"generated":[16],"by":[17,52],"a":[18,27,100,112,138],"land":[19],"surface":[20,34],"model.":[21],"We":[22,104],"calibrate":[23],"regression":[24,74,131],"algorithms":[25,132],"in":[26,111,123],"set":[28],"spatially":[30],"and":[31,48,66,81,129],"temporally":[32],"coincident":[33],"derived":[38],"from":[39],"coarse":[41],"Soil":[42],"Moisture":[43],"Active":[44],"Passive":[45],"(SMAP)":[46],"radiometer":[47],"simulated":[51],"Global":[54],"Land":[55],"Data":[56],"Assimilation":[57],"System":[58],"(GLDAS)":[59],"Noah":[60],"model,":[61],"which":[62],"assimilates":[63],"atmospheric":[64],"forcing":[65],"ancillary":[67,82],"data.":[68],"Once":[69],"calibrated,":[70],"we":[71],"apply":[72],"model":[75],"to":[76,84],"GLDAS-Noah":[78],"moisture,":[80],"data,":[83],"estimate":[85],"that":[89],"would":[90],"have":[91],"been":[92,97],"observed":[93],"if":[94],"SMAP":[95],"had":[96],"available":[98],"on":[99],"given":[101],"past":[102],"date.":[103],"explore":[105],"feasibility":[107],"approach":[110,150],"study":[113],"area":[114],"size":[116],"<tex":[117,142],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[118,143],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$12\\times":[119],"12$</tex>":[120],"degrees":[121],"located":[122],"Southern":[124],"Brazil.":[125],"The":[126],"Random":[127],"Forests":[128],"XGBoost":[130],"show":[133],"reasonable":[134],"reconstruction":[135],"skills":[136],"over":[137],"642-day":[139],"hindcast":[140],"period":[141],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(r^{2}=0.84,\\text{RMSE}=0.051\\mathrm{m}^{3}/\\mathrm{m}^{3})$</tex>":[144],".":[145],"These":[146],"results":[147],"suggest":[148],"is":[151],"worth":[152],"further":[153],"investigation.":[154]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
