{"id":"https://openalex.org/W3081407997","doi":"https://doi.org/10.1109/jstars.2020.3019046","title":"Multilevel Deep Learning Network for County-Level Corn Yield Estimation in the U.S. Corn Belt","display_name":"Multilevel Deep Learning Network for County-Level Corn Yield Estimation in the U.S. Corn Belt","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3081407997","doi":"https://doi.org/10.1109/jstars.2020.3019046","mag":"3081407997"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2020.3019046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3019046","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09177261.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09177261.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034843347","display_name":"Jie Sun","orcid":"https://orcid.org/0000-0002-5125-9149"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Sun","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006006544","display_name":"Zulong Lai","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zulong Lai","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012116347","display_name":"Liping Di","orcid":"https://orcid.org/0000-0002-3953-9965"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liping Di","raw_affiliation_strings":["Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014889794","display_name":"Ziheng Sun","orcid":"https://orcid.org/0000-0001-9810-0023"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziheng Sun","raw_affiliation_strings":["Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032217037","display_name":"Jianbin Tao","orcid":"https://orcid.org/0000-0003-4844-7736"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianbin Tao","raw_affiliation_strings":["Department of Geographic Information Sciences, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Geographic Information Sciences, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000822601","display_name":"Yonglin Shen","orcid":"https://orcid.org/0000-0001-8190-4615"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonglin Shen","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034843347"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":10.7707,"has_fulltext":true,"cited_by_count":145,"citation_normalized_percentile":{"value":0.98877122,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"13","issue":null,"first_page":"5048","last_page":"5060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.998199999332428,"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":0.998199999332428,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7368860244750977},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6940961480140686},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6797336339950562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6700310111045837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5901265144348145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5467702746391296},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4924710690975189},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.47892293334007263},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.43790143728256226},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.425346702337265},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41810816526412964},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.2236216962337494},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10179808735847473},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09979787468910217}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7368860244750977},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6940961480140686},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6797336339950562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6700310111045837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5901265144348145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5467702746391296},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4924710690975189},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.47892293334007263},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.43790143728256226},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.425346702337265},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41810816526412964},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.2236216962337494},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10179808735847473},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09979787468910217},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2020.3019046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3019046","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09177261.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f5f2df4dc47c4f2ab8a0b693fd41199c","is_oa":true,"landing_page_url":"https://doaj.org/article/f5f2df4dc47c4f2ab8a0b693fd41199c","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":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 5048-5060 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2020.3019046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3019046","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/8994817/09177261.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1356514951","display_name":null,"funder_award_id":"41971","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/G5565363648","display_name":null,"funder_award_id":"4197137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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/G8708460370","display_name":null,"funder_award_id":"41971371","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3081407997.pdf","grobid_xml":"https://content.openalex.org/works/W3081407997.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1225807830","https://openalex.org/W1660566052","https://openalex.org/W1836465849","https://openalex.org/W1968764626","https://openalex.org/W1986072339","https://openalex.org/W2014847057","https://openalex.org/W2015037454","https://openalex.org/W2027047363","https://openalex.org/W2030584283","https://openalex.org/W2112674101","https://openalex.org/W2145774049","https://openalex.org/W2187240835","https://openalex.org/W2284398832","https://openalex.org/W2290326488","https://openalex.org/W2294567968","https://openalex.org/W2337031030","https://openalex.org/W2346668369","https://openalex.org/W2523388123","https://openalex.org/W2548440765","https://openalex.org/W2588003345","https://openalex.org/W2604645045","https://openalex.org/W2618092941","https://openalex.org/W2618400371","https://openalex.org/W2805142011","https://openalex.org/W2805388006","https://openalex.org/W2809537360","https://openalex.org/W2884557755","https://openalex.org/W2885770726","https://openalex.org/W2896998982","https://openalex.org/W2902487926","https://openalex.org/W2904659464","https://openalex.org/W2917499272","https://openalex.org/W2919115771","https://openalex.org/W2921277556","https://openalex.org/W2943292975","https://openalex.org/W2944794516","https://openalex.org/W2945600159","https://openalex.org/W2949642792","https://openalex.org/W2978445197","https://openalex.org/W3103444592","https://openalex.org/W3125542187","https://openalex.org/W4244143837","https://openalex.org/W6628142984","https://openalex.org/W6637087877","https://openalex.org/W6638667902","https://openalex.org/W6696879442","https://openalex.org/W6727295702","https://openalex.org/W6735637195","https://openalex.org/W6752125693","https://openalex.org/W6892187538","https://openalex.org/W6967042277"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W2748922771","https://openalex.org/W4288388567","https://openalex.org/W4385335406"],"abstract_inverted_index":{"Accurate":[0],"and":[1,18,34,57,85,110,160,166,180,195,214,238],"timely":[2],"estimation":[3,33],"of":[4,12,104,122,216],"crop":[5],"yield":[6,32,77,201],"at":[7,206],"a":[8,42,114,152],"small":[9],"scale":[10],"is":[11,27],"great":[13],"significance":[14],"to":[15,66,94,162,198,204,241],"food":[16],"security":[17],"harvest":[19],"management.":[20],"Recent":[21],"studies":[22],"have":[23],"proven":[24],"remote":[25,72,174],"sensing":[26,73,175],"an":[28],"efficient":[29],"method":[30],"for":[31,76],"machine":[35],"learning,":[36,39],"especially":[37],"deep":[38,95,155],"can":[40,99,145],"infer":[41],"good":[43],"prediction":[44,78],"by":[45],"integrating":[46],"multisource":[47],"datasets":[48],"such":[49,235],"as":[50,236],"satellite":[51],"data,":[52,54,56,176,179],"climate":[53],"soil":[55,177],"so":[58],"on.":[59],"However,":[60],"there":[61],"are":[62],"some":[63],"bottleneck":[64],"challenges":[65],"improve":[67],"accuracy.":[68],"First,":[69],"the":[70,101,118,123,181,188,207,212,217,221,225,227],"popular":[71],"data":[74,84,105],"used":[75,196,231],"fall":[79],"into":[80],"two":[81,102],"major":[82],"groups-time-series":[83],"constant":[86],"data.":[87],"Surprisingly":[88],"little":[89],"attention":[90],"has":[91],"been":[92],"devoted":[93],"learning":[96,156],"networks":[97],"which":[98],"integrate":[100],"kinds":[103],"effectively;":[106],"second,":[107],"both":[108,164,172],"temporal":[109,140,167],"spatial":[111,147,165],"features":[112],"play":[113],"role":[115],"in":[116,190],"affecting":[117],"yields.":[119],"But":[120],"most":[121],"existing":[124],"approaches":[125],"employed":[126],"either":[127],"convolutional":[128],"neural":[129,134],"network":[130,135],"(CNN)":[131],"or":[132],"recurrent":[133],"(RNN).":[136],"CNN":[137,161],"cannot":[138],"learn":[139,146],"patterns,":[141],"while":[142],"RNN":[143,159],"barely":[144],"characteristics.":[148],"This":[149],"work":[150],"proposed":[151,218],"novel":[153],"multilevel":[154],"model":[157,182,189,228],"coupling":[158],"extract":[163],"features.":[168],"The":[169,209],"inputs":[170],"include":[171],"time-series":[173],"property":[178],"outputs":[183],"yield.":[184],"We":[185],"experimented":[186],"with":[187],"U.S.":[191],"Corn":[192],"Belt":[193],"states,":[194],"it":[197],"predict":[199],"corn":[200],"from":[202],"2013":[203],"2016":[205],"county-level.":[208],"results":[210],"approve":[211],"effectiveness":[213],"advantages":[215],"approach":[219],"over":[220],"other":[222,233],"methods.":[223],"In":[224],"future,":[226],"will":[229],"be":[230],"on":[232],"crops":[234],"soybean":[237],"winter":[239],"wheat":[240],"assist":[242],"agricultural":[243],"decision-making.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":36},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}