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A Minimum Cross-Entropy Approach to Disaggregate Agricultural Data at the Field Level

António Xavier (), Rui Fragoso (), Maria De Belém Costa Freitas (), Maria Do Socorro Rosário () and Florentino Valente ()
Additional contact information
António Xavier: CEFAGE-UE (Center for Advanced Studies in Management and Economics), Management Department, Universidade de Évora, N° 2, Apt. 95, 7002-554 Évora, Portugal
Rui Fragoso: CEFAGE-UE (Center for Advanced Studies in Management and Economics), Management Department, Universidade de Évora, N° 2, Apt. 95, 7002-554 Évora, Portugal
Maria De Belém Costa Freitas: ICAAM (Institute of Mediterranean Agricultural and Environmental Sciences), Sciences and Technology Faculty, Universidade do Algarve, Gambelas Campus, Edf. 8, 8005-139 Faro, Portugal
Maria Do Socorro Rosário: Direção de Serviços de Estatística, GPP (Gabinete de Planeamento e Políticas), Praça do Comércio, 1149-010 Lisboa, Portugal
Florentino Valente: Direção Regional de Agricultura e Pescas do Algarve, Patacão, 8001-904 Faro, Portugal

Land, 2018, vol. 7, issue 2, 1-16

Abstract: Agricultural policies have impacts on land use, the economy, and the environment and their analysis requires disaggregated data at the local level with geographical references. Thus, this study proposes a model for disaggregating agricultural data, which develops a supervised classification of satellite images by using a survey and empirical knowledge. To ensure the consistency with multiple sources of information, a minimum cross-entropy process was used. The proposed model was applied using two supervised classification algorithms and a more informative set of biophysical information. The results were validated and analyzed by considering various sources of information, showing that an entropy approach combined with supervised classifications may provide a reliable data disaggregation.

Keywords: data disaggregation; supervised classifications; classification algorithms; minimum cross-entropy; land uses; Algarve; empirical validation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:7:y:2018:i:2:p:62-:d:145362

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