文章基本信息

标题：A Minimum Cross-Entropy Approach to Disaggregate Agricultural Data at the Field Level
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作者：Xavier, António ; Fragoso, Rui ; de Belém Costa Freitas, Maria 等
期刊名称：Land
印刷版ISSN：2073-445X
出版年度：2018
卷号：7
期号：2
页码：1-16
出版社：MDPI, Open Access Journal
摘要：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.
关键词：data disaggregation; supervised classifications; classification algorithms; minimum cross-entropy; land uses; Algarve; empirical validation