{"id":"https://openalex.org/W4308509872","doi":"https://doi.org/10.3390/rs14215625","title":"Early-Season Crop Identification in the Shiyang River Basin Using a Deep Learning Algorithm and Time-Series Sentinel-2 Data","display_name":"Early-Season Crop Identification in the Shiyang River Basin Using a Deep Learning Algorithm and Time-Series Sentinel-2 Data","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308509872","doi":"https://doi.org/10.3390/rs14215625"},"language":"en","primary_location":{"id":"doi:10.3390/rs14215625","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215625","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5625/pdf?version=1667834779","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/2072-4292/14/21/5625/pdf?version=1667834779","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047607105","display_name":"Zhiwei Yi","orcid":"https://orcid.org/0000-0001-9247-6521"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Yi","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405681","display_name":"Jia Li","orcid":"https://orcid.org/0000-0002-3108-8645"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Jia","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033553593","display_name":"Qiting Chen","orcid":"https://orcid.org/0000-0001-6588-0131"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiting Chen","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049680425","display_name":"Min Jiang","orcid":"https://orcid.org/0000-0002-3510-9829"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Jiang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005218250","display_name":"Dingwang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingwang Zhou","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078443769","display_name":"Yelong Zeng","orcid":"https://orcid.org/0000-0003-4294-2453"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yelong Zeng","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5033553593"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199","https://openalex.org/I4210166112"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.2441,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.94404035,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"14","issue":"21","first_page":"5625","last_page":"5625"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9976999759674072,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6964109539985657},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6754170060157776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758612751960754},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5387763381004333},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5211848616600037},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49165254831314087},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4864213466644287},{"id":"https://openalex.org/keywords/growing-season","display_name":"Growing season","score":0.47720465064048767},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45382487773895264},{"id":"https://openalex.org/keywords/warning-system","display_name":"Warning system","score":0.4488829970359802},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.43024155497550964},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.08128350973129272}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6964109539985657},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6754170060157776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758612751960754},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5387763381004333},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5211848616600037},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49165254831314087},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4864213466644287},{"id":"https://openalex.org/C137660486","wikidata":"https://www.wikidata.org/wiki/Q732240","display_name":"Growing season","level":2,"score":0.47720465064048767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45382487773895264},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.4488829970359802},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.43024155497550964},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.08128350973129272},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14215625","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215625","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5625/pdf?version=1667834779","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:90f941c357c74c02b6896413f3d96bbe","is_oa":true,"landing_page_url":"https://doaj.org/article/90f941c357c74c02b6896413f3d96bbe","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 21, p 5625 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/21/5625/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14215625","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 21; Pages: 5625","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14215625","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215625","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5625/pdf?version=1667834779","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":[{"score":0.49000000953674316,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G495064427","display_name":null,"funder_award_id":"XDA19030203","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"}],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308509872.pdf","grobid_xml":"https://content.openalex.org/works/W4308509872.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1991361881","https://openalex.org/W1995378944","https://openalex.org/W1998281138","https://openalex.org/W2000613913","https://openalex.org/W2008085934","https://openalex.org/W2018636632","https://openalex.org/W2021662310","https://openalex.org/W2039598117","https://openalex.org/W2040667072","https://openalex.org/W2062321700","https://openalex.org/W2063479531","https://openalex.org/W2067055509","https://openalex.org/W2068094410","https://openalex.org/W2069143585","https://openalex.org/W2081345410","https://openalex.org/W2082874195","https://openalex.org/W2088666544","https://openalex.org/W2090116710","https://openalex.org/W2090231298","https://openalex.org/W2101234009","https://openalex.org/W2168481151","https://openalex.org/W2273708466","https://openalex.org/W2325718943","https://openalex.org/W2407655494","https://openalex.org/W2464130106","https://openalex.org/W2561750000","https://openalex.org/W2578830027","https://openalex.org/W2583513334","https://openalex.org/W2610947800","https://openalex.org/W2730238284","https://openalex.org/W2745131289","https://openalex.org/W2791592925","https://openalex.org/W2805461187","https://openalex.org/W2883026662","https://openalex.org/W2903282641","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2950314938","https://openalex.org/W2953757725","https://openalex.org/W2972084355","https://openalex.org/W2976696463","https://openalex.org/W2997168047","https://openalex.org/W2999712229","https://openalex.org/W3001402238","https://openalex.org/W3033448968","https://openalex.org/W3037002701","https://openalex.org/W3089038181","https://openalex.org/W3090592965","https://openalex.org/W3096477768","https://openalex.org/W3100996084","https://openalex.org/W3182299891","https://openalex.org/W3205696749","https://openalex.org/W4210692134","https://openalex.org/W4239510810","https://openalex.org/W4244713694","https://openalex.org/W4296776311","https://openalex.org/W6675354045","https://openalex.org/W6753602705"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W1924178503","https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645"],"abstract_inverted_index":{"Timely":[0],"and":[1,5,17,29,51,83,91,107,109,113,122,133,146,161,203,220,224,244,292,301,322,330,339],"accurate":[2],"crop":[3,12,21,68,89,93,174,193,217,228,259,328,344],"identification":[4,22,90,218,229,255,345],"mapping":[6,230],"are":[7],"of":[8,31,48,54,80,198,242,317],"great":[9,40],"significance":[10],"for":[11,66,87,149,171,257,341],"yield":[13],"estimation,":[14],"disaster":[15],"warning,":[16],"food":[18],"security.":[19],"Early-season":[20],"places":[23],"higher":[24,59],"demands":[25],"on":[26],"the":[27,46,52,78,152,168,172,181,186,196,210,215,226,233,240,245,253,263,267,272,276,281,285,290,296,302,306,315],"quality":[28],"mining":[30],"time-series":[32,84,206,320],"information":[33],"than":[34],"post-season":[35],"mapping.":[36,94],"In":[37,70,95,251],"recent":[38],"years,":[39],"strides":[41],"have":[42],"been":[43],"made":[44],"in":[45,137,151,191,213,232,266,275,284,295,305],"development":[47],"deep-learning":[49,81,102,183,323],"algorithms,":[50],"emergence":[53],"Sentinel-2":[55,85,131,207,319],"data":[56,86,208,321],"with":[57,158],"a":[58,123,199],"temporal":[60],"resolution":[61],"has":[62],"provided":[63],"new":[64,337],"opportunities":[65],"early-season":[67,88,92,130,192,216,227,327,343],"identification.":[69,175],"this":[71,96,331],"study,":[72,97],"we":[73],"aimed":[74],"to":[75,144,166,325,335],"fully":[76],"exploit":[77],"potential":[79,316],"algorithms":[82,103,117,141,184,190,324],"four":[98],"classifiers,":[99],"i.e.,":[100],"two":[101,114,182,187],"(one-dimensional":[104],"convolutional":[105,201],"networks":[106],"long":[108],"short-term":[110],"memory":[111],"networks)":[112],"shallow":[115,188],"machine-learning":[116,189],"(a":[118],"random":[119],"forest":[120],"algorithm":[121],"support":[124],"vector":[125],"machine),":[126],"were":[127,142,164,294,304],"trained":[128],"using":[129,318],"images":[132,145],"field":[134,147],"samples":[135,148],"collected":[136],"2019.":[138],"Then,":[139],"these":[140],"applied":[143],"2020":[150],"Shiyang":[153,234],"River":[154,235],"Basin.":[155],"Twelve":[156],"scenarios":[157],"different":[159],"classifiers":[160],"time":[162,219,231,256],"intervals":[163],"compared":[165],"determine":[167],"optimal":[169],"combination":[170,197],"earliest":[173],"The":[176],"results":[177],"show":[178],"that:":[179],"(1)":[180],"outperformed":[185,209],"identification;":[194],"(2)":[195],"one-dimensional":[200],"network":[202],"5-day":[204],"interval":[205],"other":[211],"schemes":[212],"obtaining":[214],"achieving":[221],"early":[222,254,286],"mapping;":[223],"(3)":[225],"Basin":[236],"was":[237,260,265,274,283],"identified":[238],"as":[239,261],"end":[241],"July,":[243],"overall":[246],"classification":[247],"accuracy":[248],"reached":[249],"0.83.":[250],"addition,":[252],"each":[258],"follows:":[262],"wheat":[264],"flowering":[268,297],"stage":[269,288,298,308],"(mid-late":[270,279],"June);":[271,280],"alfalfa":[273],"first":[277],"harvest":[278],"corn":[282],"tassel":[287],"(mid-July);":[289],"fennel":[291],"sunflower":[293],"(late":[299],"July);":[300],"melons":[303],"fruiting":[307],"(around":[309],"late":[310],"July).":[311],"This":[312],"study":[313],"demonstrates":[314],"achieve":[326],"identification,":[329],"method":[332],"is":[333],"expected":[334],"provide":[336],"solutions":[338],"ideas":[340],"addressing":[342],"monitoring.":[346]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
