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Mainly cultivated in tropical and subtropical countries, such as Brazil, India, and China, this crop presented a global harvested area of 17.4 million hectares (Mha) in 2021. Thus, decision making in this activity needs reliable information. Obtaining accurate sugarcane yield estimates is challenging, and in this sense, it is important to reduce uncertainties. Currently, it can be estimated by empirical or mechanistic approaches. However, the model\u2019s peculiarities vary according to the availability of data and the spatial scale. Here, we present a systematic review to discuss state-of-the-art sugarcane yield estimation approaches using remote sensing and crop simulation models. We consulted 1398 papers, and we focused on 72 of them, published between January 2017 and June 2023 in the main scientific databases (e.g., AGORA-FAO, Google Scholar, Nature, MDPI, among others), using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. We observed how the models vary in space and time, presenting the potential, challenges, limitations, and outlooks for enhancing decision making in the sugarcane crop supply chain. We concluded that remote sensing data assimilation both in mechanistic and empirical models is promising and will be enhanced in the coming years, due to the increasing availability of free Earth observation data.<\/jats:p>","DOI":"10.3390\/rs16050863","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T07:36:21Z","timestamp":1709278581000},"page":"863","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Sugarcane Yield Estimation Using Satellite Remote Sensing Data in Empirical or Mechanistic Modeling: A Systematic Review"],"prefix":"10.3390","volume":"16","author":[{"given":"Nildson Rodrigues","family":"de Fran\u00e7a e Silva","sequence":"first","affiliation":[{"name":"Remote Sensing Postgraduate Program (PGSER), Coordination of Teaching, Research and Extension (COEPE), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1498-6830","authenticated-orcid":false,"given":"Michel Eust\u00e1quio Dantas","family":"Chaves","sequence":"additional","affiliation":[{"name":"S\u00e3o Paulo State University (Unesp), School of Sciences and Engineering, Tup\u00e3 17602-496, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4862-9863","authenticated-orcid":false,"given":"Ana Cl\u00e1udia dos Santos","family":"Luciano","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering, Graduate School of Agriculture Luiz de Queiroz (ESALQ), University of S\u00e3o Paulo (USP), Piracicaba 13418-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1296-0933","authenticated-orcid":false,"given":"Ieda Del\u2019Arco","family":"Sanches","sequence":"additional","affiliation":[{"name":"Remote Sensing Postgraduate Program (PGSER), Coordination of Teaching, Research and Extension (COEPE), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"Earth Observation and Geoinformatics Division (DIOTG), General Coordination of Earth Science (CG-CT), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6523-3169","authenticated-orcid":false,"given":"Cl\u00e1udia Maria","family":"de Almeida","sequence":"additional","affiliation":[{"name":"Remote Sensing Postgraduate Program (PGSER), Coordination of Teaching, Research and Extension (COEPE), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"Earth Observation and Geoinformatics Division (DIOTG), General Coordination of Earth Science (CG-CT), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4247-4477","authenticated-orcid":false,"given":"Marcos","family":"Adami","sequence":"additional","affiliation":[{"name":"Remote Sensing Postgraduate Program (PGSER), Coordination of Teaching, Research and Extension (COEPE), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"Earth Observation and Geoinformatics Division (DIOTG), General Coordination of Earth Science (CG-CT), National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.eja.2018.01.005","article-title":"Predicting Genotypic Differences in Irrigated Sugarcane Yield Using the Canegro Model and Independent Trait Parameter Estimates","volume":"96","author":"Hoffman","year":"2018","journal-title":"Eur. 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