Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/24529

Title: A Minimum Cross-Entropy Approach to Disaggregate Agricultural Data at the Field Level
Authors: Xavier, António
Fragoso, Rui
Costa Freitas, Maria de Belém
Rosário, Maria do Socorro
Valente, Florentino
Keywords: data disaggregation
supervised classifications
minimum cross-entropy
land uses
Algarve
empirical validation
Issue Date: 2018
Citation: Xavier, A., R. Fragoso, M.B.C. Freitas, M.S. Rosário, F. Valente (2018), "A Minimum Cross-Entropy Approach to Disaggregate Agricultural Data at the Field Level", Land, 7(2), 62.
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.
URI: http://hdl.handle.net/10174/24529
Type: article
Appears in Collections:ICAAM - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
GES - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
ECN - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
CEFAGE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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