{"id":"https://openalex.org/W4307548948","doi":"https://doi.org/10.3390/rs14205280","title":"Developing a Dual-Stream Deep-Learning Neural Network Model for Improving County-Level Winter Wheat Yield Estimates in China","display_name":"Developing a Dual-Stream Deep-Learning Neural Network Model for Improving County-Level Winter Wheat Yield Estimates in China","publication_year":2022,"publication_date":"2022-10-21","ids":{"openalex":"https://openalex.org/W4307548948","doi":"https://doi.org/10.3390/rs14205280"},"language":"en","primary_location":{"id":"doi:10.3390/rs14205280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205280","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5280/pdf?version=1666690927","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/2072-4292/14/20/5280/pdf?version=1666690927","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101522193","display_name":"Hai Huang","orcid":"https://orcid.org/0000-0002-4099-8675"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Huang","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0002-4099-8675","affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046271690","display_name":"Jianxi Huang","orcid":"https://orcid.org/0000-0003-0341-1983"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianxi Huang","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China","Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0003-0341-1983","affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078340301","display_name":"Quanlong Feng","orcid":"https://orcid.org/0000-0002-0569-4131"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanlong Feng","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China","Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102863611","display_name":"Junming Liu","orcid":"https://orcid.org/0000-0002-9301-0894"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junming Liu","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China","Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011145539","display_name":"Xuecao Li","orcid":"https://orcid.org/0000-0002-6942-0746"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuecao Li","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China","Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0002-6942-0746","affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100722141","display_name":"Xinlei Wang","orcid":"https://orcid.org/0000-0002-6542-3333"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlei Wang","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061988032","display_name":"Quandi Niu","orcid":"https://orcid.org/0000-0002-9576-5350"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quandi Niu","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046271690"],"corresponding_institution_ids":["https://openalex.org/I4210151987","https://openalex.org/I52158045"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":3.5231,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.92957402,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"14","issue":"20","first_page":"5280","last_page":"5280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9961000084877014,"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":0.9771999716758728,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5891788601875305},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5810744166374207},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5312333703041077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47254395484924316},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.430738627910614},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.42772069573402405},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.42417043447494507},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40525496006011963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39660072326660156},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3569151759147644},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14418601989746094}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5891788601875305},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5810744166374207},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5312333703041077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47254395484924316},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.430738627910614},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.42772069573402405},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.42417043447494507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40525496006011963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39660072326660156},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3569151759147644},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14418601989746094},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14205280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205280","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5280/pdf?version=1666690927","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:b5f0ea27d2c4457b91bcd4aa0417c3d8","is_oa":true,"landing_page_url":"https://doaj.org/article/b5f0ea27d2c4457b91bcd4aa0417c3d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 14, Iss 20, p 5280 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/20/5280/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14205280","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 14; Issue 20; Pages: 5280","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14205280","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205280","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5280/pdf?version=1666690927","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":[{"display_name":"Zero hunger","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G2693478763","display_name":null,"funder_award_id":"No. 41971383","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3549628271","display_name":"\u540c\u5316\u65e5\u5149\u8bf1\u5bfc\u53f6\u7eff\u7d20\u8367\u5149\u9065\u611f\u6570\u636e\u4e0e\u673a\u7406\u8fc7\u7a0b\u6a21\u578b\u7684\u533a\u57df\u51ac\u5c0f\u9ea6\u4ea7\u91cf\u9884\u6d4b\u7814\u7a76","funder_award_id":"41971383","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5649895828","display_name":null,"funder_award_id":"42271339","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4307548948.pdf","grobid_xml":"https://content.openalex.org/works/W4307548948.grobid-xml"},"referenced_works_count":88,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1677182931","https://openalex.org/W1903029394","https://openalex.org/W1967135612","https://openalex.org/W1979636379","https://openalex.org/W1986072339","https://openalex.org/W1987415163","https://openalex.org/W1997641853","https://openalex.org/W2010806274","https://openalex.org/W2012642412","https://openalex.org/W2014847057","https://openalex.org/W2017555282","https://openalex.org/W2021662310","https://openalex.org/W2021954052","https://openalex.org/W2056251274","https://openalex.org/W2057891673","https://openalex.org/W2062044208","https://openalex.org/W2069384557","https://openalex.org/W2075844317","https://openalex.org/W2087506358","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2131095795","https://openalex.org/W2136939460","https://openalex.org/W2161557312","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2202019762","https://openalex.org/W2212980623","https://openalex.org/W2523192248","https://openalex.org/W2588003345","https://openalex.org/W2604645045","https://openalex.org/W2605145284","https://openalex.org/W2610947800","https://openalex.org/W2737725206","https://openalex.org/W2752782242","https://openalex.org/W2754887531","https://openalex.org/W2762524281","https://openalex.org/W2790796805","https://openalex.org/W2803946774","https://openalex.org/W2805142011","https://openalex.org/W2808998299","https://openalex.org/W2809537360","https://openalex.org/W2810004461","https://openalex.org/W2810601729","https://openalex.org/W2886775386","https://openalex.org/W2900420505","https://openalex.org/W2902487926","https://openalex.org/W2903282641","https://openalex.org/W2905983018","https://openalex.org/W2913323966","https://openalex.org/W2919115771","https://openalex.org/W2921277556","https://openalex.org/W2921360674","https://openalex.org/W2936990419","https://openalex.org/W2943214363","https://openalex.org/W2944794516","https://openalex.org/W2953807054","https://openalex.org/W2962325202","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2964199361","https://openalex.org/W2990480734","https://openalex.org/W2997552745","https://openalex.org/W3002343708","https://openalex.org/W3029014910","https://openalex.org/W3037002701","https://openalex.org/W3090239664","https://openalex.org/W3111700100","https://openalex.org/W3122287636","https://openalex.org/W3185118158","https://openalex.org/W3198376164","https://openalex.org/W3205788253","https://openalex.org/W4280594086","https://openalex.org/W4281250178","https://openalex.org/W4281686257","https://openalex.org/W4283690132","https://openalex.org/W4294864637","https://openalex.org/W4296776311","https://openalex.org/W6618372016","https://openalex.org/W6674330103","https://openalex.org/W6680230698","https://openalex.org/W6684191040","https://openalex.org/W6743446608","https://openalex.org/W6748965087","https://openalex.org/W6784345608","https://openalex.org/W6838147226"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2386800167","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W2384315363","https://openalex.org/W2317351040","https://openalex.org/W4383066092"],"abstract_inverted_index":{"Accurate":[0],"and":[1,16,41,57,92,96,125,147,159,193],"timely":[2],"crop":[3,26],"yield":[4,27,173],"prediction":[5,28],"over":[6,29,215],"large":[7,31,216],"spatial":[8,32,217],"regions":[9],"is":[10],"critical":[11],"to":[12,37,117,155,182,206],"national":[13],"food":[14],"security":[15],"sustainable":[17],"agricultural":[18],"development.":[19],"However,":[20],"designing":[21],"a":[22,30,62,148,203],"robust":[23,83],"model":[24,67,77,116,128,140,169],"for":[25,68,82,87,99],"region":[33],"remains":[34],"challenging":[35],"due":[36],"inadequate":[38],"surveyed":[39],"samples":[40],"an":[42,113,142,176],"under-development":[43],"of":[44,79,134,145,151,178],"deep-learning":[45,64,166],"frameworks.":[46],"To":[47],"tackle":[48],"this":[49],"issue,":[50],"we":[51],"integrated":[52],"multi-source":[53,197],"(remote":[54,90],"sensing,":[55],"weather,":[56],"soil":[58],"properties)":[59],"data":[60,89,101],"into":[61],"dual-stream":[63,165],"neural":[65,167],"network":[66,168],"winter":[69,136,208],"wheat":[70,121,137,209],"in":[71],"China\u2019s":[72],"major":[73],"planting":[74],"regions.":[75,218],"The":[76,104,139,164],"consists":[78],"two":[80,186],"branches":[81,109],"feature":[84],"learning:":[85],"one":[86],"sequential":[88],"sensing":[91],"weather":[93],"series":[94],"data)":[95],"the":[97,119,127,156,199,212],"other":[98],"statical":[100],"(soil":[102],"properties).":[103],"extracted":[105],"features":[106,195],"by":[107,129],"both":[108],"were":[110],"aggregated":[111],"through":[112],"adaptive":[114],"fusion":[115],"forecast":[118],"final":[120],"yield.":[122],"We":[123],"trained":[124],"tested":[126],"using":[130],"official":[131,183],"county-level":[132],"statistics":[133,184],"historical":[135],"yields.":[138],"achieved":[141],"average":[143],"R2":[144],"0.79":[146],"root-mean-square":[149],"error":[150,177],"650.21":[152],"kg/ha,":[153],"superior":[154],"compared":[157,181],"methods":[158],"outperforming":[160],"traditional":[161],"machine-learning":[162],"methods.":[163],"provided":[170],"decent":[171],"in-season":[172],"prediction,":[174],"with":[175],"about":[179,185],"13%":[180],"months":[187],"before":[188],"harvest.":[189],"By":[190],"effectively":[191],"extracting":[192],"aggregating":[194],"from":[196],"datasets,":[198],"new":[200],"approach":[201,205],"provides":[202],"practical":[204],"predicting":[207],"yields":[210],"at":[211],"county":[213],"scale":[214]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
