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However, there is no evidence of their widespread use by policymakers. Here, we carry out a review of LU ABMs to understand how farmers\u2019 decision-making has been modelled. We found that LU ABMs mainly rely on pre-defined behavioural rules at the individual farmers\u2019 level. They prioritise explanatory over predictive purposes, thus limiting the use of ABM for policy assessment. We explore the use of machine learning (ML) as a data-driven alternative for modelling decisions. Integration of ML with ABMs has never been properly applied to LU modelling, despite the increased availability of remote sensing products and agricultural micro-data. Therefore, we also propose a framework to develop data-driven ABMs for agricultural LU. This framework avoids pre-defined theoretical or heuristic rules and instead resorts to ML algorithms to learn agents\u2019 behavioural rules from data. ML models are not directly interpretable, but their analysis can provide novel insights regarding the response of farmers to policy changes. The integration of ML models can also improve the validation of individual behaviours, which increases the ability of ABMs to predict policy outcomes at the micro-level.<\/jats:p>","DOI":"10.3390\/land12040756","type":"journal-article","created":{"date-parts":[[2023,3,27]],"date-time":"2023-03-27T07:32:09Z","timestamp":1679902329000},"page":"756","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["A Framework for Data-Driven Agent-Based Modelling of Agricultural Land Use"],"prefix":"10.3390","volume":"12","author":[{"given":"Giacomo","family":"Ravaioli","sequence":"first","affiliation":[{"name":"MARETEC-Marine, Environment and Technology Centre, LARSyS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6194-0405","authenticated-orcid":false,"given":"Tiago","family":"Domingos","sequence":"additional","affiliation":[{"name":"MARETEC-Marine, Environment and Technology Centre, LARSyS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9915-6264","authenticated-orcid":false,"given":"Ricardo F. M.","family":"Teixeira","sequence":"additional","affiliation":[{"name":"MARETEC-Marine, Environment and Technology Centre, LARSyS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.ecolecon.2016.12.027","article-title":"Ecological Macroeconomic Models: Assessing Current Developments","volume":"134","author":"Hardt","year":"2017","journal-title":"Ecol. Econ."},{"key":"ref_2","unstructured":"Raworth, K. (2012). Oxfam."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/S0140-6736(18)31788-4","article-title":"Food in the Anthropocene: The EAT\u2013Lancet Commission on Healthy Diets from Sustainable Food Systems","volume":"393","author":"Willett","year":"2019","journal-title":"Lancet"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1146\/annurev-environ-020411-130608","article-title":"Climate Change and Food Systems","volume":"37","author":"Vermeulen","year":"2012","journal-title":"Annu. Rev. Environ. 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