{"id":"https://openalex.org/W4206381465","doi":"https://doi.org/10.3390/s22030717","title":"Evaluation of Random Forests (RF) for Regional and Local-Scale Wheat Yield Prediction in Southeast Australia","display_name":"Evaluation of Random Forests (RF) for Regional and Local-Scale Wheat Yield Prediction in Southeast Australia","publication_year":2022,"publication_date":"2022-01-18","ids":{"openalex":"https://openalex.org/W4206381465","doi":"https://doi.org/10.3390/s22030717","pmid":"https://pubmed.ncbi.nlm.nih.gov/35161467"},"language":"en","primary_location":{"id":"doi:10.3390/s22030717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030717","pdf_url":"https://www.mdpi.com/1424-8220/22/3/717/pdf?version=1642508490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/3/717/pdf?version=1642508490","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068838448","display_name":"Alexis Pang","orcid":"https://orcid.org/0000-0003-3929-3456"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I4210138055","display_name":"Agriculture and Food","ror":"https://ror.org/03n17ds51","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210138055","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Alexis Pang","raw_affiliation_strings":["School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3929-3456","affiliations":[{"raw_affiliation_string":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia","institution_ids":["https://openalex.org/I165779595","https://openalex.org/I4210138055"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030246979","display_name":"Melissa W L Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I4210138055","display_name":"Agriculture and Food","ror":"https://ror.org/03n17ds51","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210138055","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I88943931","display_name":"Agri-Food and Veterinary Authority of Singapore","ror":"https://ror.org/04afrdx88","country_code":"SG","type":"government","lineage":["https://openalex.org/I4210154943","https://openalex.org/I88943931"]}],"countries":["AU","SG"],"is_corresponding":false,"raw_author_name":"Melissa W L Chang","raw_affiliation_strings":["School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia","Singapore Food Agency, JEM Office Tower, 52 Jurong Gateway Road, #14-01, Singapore 608550, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia","institution_ids":["https://openalex.org/I165779595","https://openalex.org/I4210138055"]},{"raw_affiliation_string":"Singapore Food Agency, JEM Office Tower, 52 Jurong Gateway Road, #14-01, Singapore 608550, Singapore","institution_ids":["https://openalex.org/I88943931"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020522391","display_name":"Yang Chen","orcid":"https://orcid.org/0000-0003-2343-7443"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I4210138055","display_name":"Agriculture and Food","ror":"https://ror.org/03n17ds51","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210138055","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Chen","raw_affiliation_strings":["CSIRO Data61, Goods Shed North, 34 Village St., Docklands 3008, Australia","School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2343-7443","affiliations":[{"raw_affiliation_string":"CSIRO Data61, Goods Shed North, 34 Village St., Docklands 3008, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]},{"raw_affiliation_string":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville 3010, Australia","institution_ids":["https://openalex.org/I165779595","https://openalex.org/I4210138055"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068838448"],"corresponding_institution_ids":["https://openalex.org/I165779595","https://openalex.org/I4210138055"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":11.1812,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":{"value":0.98939858,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"22","issue":"3","first_page":"717","last_page":"717"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9983999729156494,"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":0.9983999729156494,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9821000099182129,"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/random-forest","display_name":"Random forest","score":0.7964733839035034},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.6472671031951904},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6079293489456177},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5153610110282898},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.5052967667579651},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.472819447517395},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4636152386665344},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.4540007412433624},{"id":"https://openalex.org/keywords/growing-season","display_name":"Growing season","score":0.44972869753837585},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.44134026765823364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42560431361198425},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.419276624917984},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.4153313934803009},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3908922076225281},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3635219931602478},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.3243616223335266},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.25069260597229004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.1884518563747406},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.1874203383922577},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15985125303268433}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7964733839035034},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.6472671031951904},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6079293489456177},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5153610110282898},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.5052967667579651},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.472819447517395},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4636152386665344},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.4540007412433624},{"id":"https://openalex.org/C137660486","wikidata":"https://www.wikidata.org/wiki/Q732240","display_name":"Growing season","level":2,"score":0.44972869753837585},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.44134026765823364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42560431361198425},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.419276624917984},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4153313934803009},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3908922076225281},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3635219931602478},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.3243616223335266},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.25069260597229004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.1884518563747406},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.1874203383922577},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15985125303268433},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D001315","descriptor_name":"Australia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001315","descriptor_name":"Australia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001315","descriptor_name":"Australia","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012621","descriptor_name":"Seasons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012621","descriptor_name":"Seasons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012621","descriptor_name":"Seasons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014908","descriptor_name":"Triticum","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014908","descriptor_name":"Triticum","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014908","descriptor_name":"Triticum","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055904","descriptor_name":"Meteorology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055904","descriptor_name":"Meteorology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055904","descriptor_name":"Meteorology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063809","descriptor_name":"Satellite Imagery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D063809","descriptor_name":"Satellite Imagery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D063809","descriptor_name":"Satellite Imagery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22030717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030717","pdf_url":"https://www.mdpi.com/1424-8220/22/3/717/pdf?version=1642508490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:35161467","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35161467","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:8de15503d17148dc863062b0900b2906","is_oa":true,"landing_page_url":"https://doaj.org/article/8de15503d17148dc863062b0900b2906","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":"Sensors, Vol 22, Iss 3, p 717 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/3/717/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22030717","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":"Sensors; Volume 22; Issue 3; Pages: 717","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8839090","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8839090","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22030717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22030717","pdf_url":"https://www.mdpi.com/1424-8220/22/3/717/pdf?version=1642508490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4206381465.pdf"},"referenced_works_count":79,"referenced_works":["https://openalex.org/W1536061269","https://openalex.org/W1614886892","https://openalex.org/W1662323679","https://openalex.org/W1852243298","https://openalex.org/W1963519462","https://openalex.org/W1965106709","https://openalex.org/W1975813392","https://openalex.org/W1984677551","https://openalex.org/W1987415163","https://openalex.org/W2001909837","https://openalex.org/W2004303413","https://openalex.org/W2010308608","https://openalex.org/W2018627383","https://openalex.org/W2040417533","https://openalex.org/W2041054901","https://openalex.org/W2048697945","https://openalex.org/W2077766806","https://openalex.org/W2095649738","https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2101824565","https://openalex.org/W2118349863","https://openalex.org/W2137963769","https://openalex.org/W2188115011","https://openalex.org/W2188767531","https://openalex.org/W2196514219","https://openalex.org/W2304701967","https://openalex.org/W2317582304","https://openalex.org/W2337031030","https://openalex.org/W2399009951","https://openalex.org/W2416782259","https://openalex.org/W2523311857","https://openalex.org/W2617564741","https://openalex.org/W2790979755","https://openalex.org/W2795018073","https://openalex.org/W2803315948","https://openalex.org/W2805837072","https://openalex.org/W2807302256","https://openalex.org/W2843415492","https://openalex.org/W2883603735","https://openalex.org/W2884755677","https://openalex.org/W2885770726","https://openalex.org/W2888753230","https://openalex.org/W2892959751","https://openalex.org/W2894225610","https://openalex.org/W2898710507","https://openalex.org/W2910729503","https://openalex.org/W2911964244","https://openalex.org/W2913130920","https://openalex.org/W2929349101","https://openalex.org/W2937840076","https://openalex.org/W2940995511","https://openalex.org/W2984188094","https://openalex.org/W2997735699","https://openalex.org/W2998970104","https://openalex.org/W2999658315","https://openalex.org/W3001084290","https://openalex.org/W3005029250","https://openalex.org/W3008377856","https://openalex.org/W3017127038","https://openalex.org/W3075397214","https://openalex.org/W3079760979","https://openalex.org/W3092909554","https://openalex.org/W3122790351","https://openalex.org/W3129445875","https://openalex.org/W3131716080","https://openalex.org/W3133892889","https://openalex.org/W3135871359","https://openalex.org/W3161294357","https://openalex.org/W3167890515","https://openalex.org/W3192357214","https://openalex.org/W3201452552","https://openalex.org/W4212883601","https://openalex.org/W6653296783","https://openalex.org/W6655012520","https://openalex.org/W6674385629","https://openalex.org/W6675354045","https://openalex.org/W6677707291","https://openalex.org/W6753199821"],"related_works":["https://openalex.org/W2360471910","https://openalex.org/W2996115036","https://openalex.org/W3080397319","https://openalex.org/W3096013024","https://openalex.org/W1964538194","https://openalex.org/W2415170322","https://openalex.org/W2161881124","https://openalex.org/W2969072466","https://openalex.org/W2391543016","https://openalex.org/W2046550984"],"abstract_inverted_index":{"Wheat":[0],"accounts":[1],"for":[2,39,76,139,154,170,200,235],"more":[3,40],"than":[4],"50%":[5],"of":[6,24,224],"Australia\u2019s":[7],"total":[8],"grain":[9],"production.":[10],"The":[11,29,148],"capability":[12],"to":[13,64,126],"generate":[14],"accurate":[15],"in-season":[16],"yield":[17,33,69,97,122,241],"predictions":[18],"is":[19],"important":[20],"across":[21],"all":[22],"components":[23],"the":[25,37,73,131,155,222],"agricultural":[26],"value":[27],"chain.":[28],"literature":[30],"on":[31,228],"wheat":[32],"prediction":[34,70,153],"has":[35],"motivated":[36],"need":[38],"novel":[41],"works":[42],"evaluating":[43],"machine":[44],"learning":[45],"techniques":[46],"such":[47],"as":[48,237,239],"random":[49],"forests":[50],"(RF)":[51],"at":[52,72,133],"multiple":[53],"scales.":[54],"This":[55,219],"research":[56],"applied":[57],"a":[58],"Random":[59],"Forest":[60],"Regression":[61],"(RFR)":[62],"technique":[63],"build":[65],"regional":[66,236],"and":[67,91,121,129,144,183,215,231],"local-scale":[68,240],"models":[71,132,169],"pixel":[74,134],"level":[75,135],"three":[77,156],"southeast":[78],"Australian":[79],"wheat-growing":[80],"paddocks,":[81],"each":[82],"located":[83],"in":[84,173],"Victoria":[85],"(VIC),":[86],"New":[87],"South":[88,92],"Wales":[89],"(NSW)":[90],"Australia":[93],"(SA)":[94],"using":[95,136],"2018":[96],"maps":[98],"from":[99,113],"data":[100,111,123],"supplied":[101],"by":[102],"collaborating":[103],"farmers.":[104],"Time-series":[105],"Normalized":[106],"Difference":[107],"Vegetation":[108],"Index":[109],"(NDVI)":[110],"derived":[112],"Planet\u2019s":[114],"high":[115,211],"spatio-temporal":[116],"resolution":[117],"imagery,":[118],"meteorological":[119],"variables":[120],"were":[124,213],"used":[125],"train,":[127],"test":[128],"validate":[130],"Python":[137],"libraries":[138],"(a)":[140],"regional-scale":[141],"three-paddock":[142],"composite":[143,149],"(b)":[145],"individual":[146,171],"paddocks.":[147],"region-wide":[150],"RF":[151,168,226],"model":[152],"paddocks":[157,172],"performed":[158,193],"well":[159,238],"(R2":[160,175,185,202],"=":[161,164,176,179,186,189,203,206],"0.86,":[162],"RMSE":[163,178,188,205],"0.18":[165],"t":[166,181,191,208],"ha\u22121).":[167,209],"VIC":[174],"0.89,":[177],"0.15":[180],"ha\u22121)":[182,192],"NSW":[184],"0.87,":[187],"0.07":[190],"well,":[194],"but":[195],"moderate":[196],"performance":[197],"was":[198],"seen":[199],"SA":[201],"0.45,":[204],"0.25":[207],"Generally,":[210],"values":[212,217],"underpredicted":[214],"low":[216],"overpredicted.":[218],"study":[220],"demonstrated":[221],"feasibility":[223],"applying":[225],"modeling":[227],"satellite":[229],"imagery":[230],"yielded":[232],"\u2018big":[233],"data\u2019":[234],"prediction.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
