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Ferreira da Silva da Costa Freitas, Maria de Belém
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- An approach using entropy and supervised classifications to disaggregate agricultural data at a local levelPublication . Xavier, Antonio; Fragoso, Rui; Costa Freitas, M. B.; Rosario, Maria do SocorroChanges in the Common Agricultural Policy (CAP) had several consequences on land-use and on the environment. This calls for detailed disaggregated agricultural data with precise geographical references. To tackle such problems data disaggregation processes are needed and a series of studies are being carried out at international level, which still have not taken the utmost advantage of remote sensing technologies by combining them with mathematical programming methods, namely entropy. Therefore, the objective of this article was to provide an approach to disaggregate agricultural data at the local level, taking advantage of the existent up-to-date satellite imagery and an entropy approach for manage different sets of data. The results were compared with other approaches and showed to be coherent, and may be improved further with the inclusion of other information.
- A minimum cross entropy approach to disaggregate agricultural data at the field levelPublication . Xavier, Antonio; Fragoso, Rui; Costa Freitas, M. B.; Rosario, Maria do Socorro; Valente, FlorentinoAgricultural 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.
- An integrated decision support system for the Mediterranean forestsPublication . Costa Freitas, M. B.; Xavier, António; Fragoso, R.Mediterranean forests contain a relevant biological diversity and are relevant for local economy. However, they are subject to various risks, particularly the risk of forest fires. This turns the critical decisions of forest managers, affecting both the long-term future of the forest and daily activities, to be difficult. To simulate decisions, and help managers and policy makers, a decision support system, which integrates the biological, environmental and economic management perspectives of agricultural and forest areas, was developed and considers the activities existing in the territory. The decision support system considers the characteristics of the biophysical units that comprise the territorial study area, production technologies and conservation of agro-forestry goods and preferences of managers or stakeholders. The proposed approach was applied in a pilot Forest Intervention Zone (FIZ) located within the Algarve region inner land. The results show that the decision support system proposed is an important tool for managing the territory and for implementing the manager's decisions. (C) 2015 Elsevier Ltd. All rights reserved.