Research Article Disaggregation of Statistical Livestock Data Using the Entropy Approach António Xavier, 1 Maria de Belém Costa Freitas, 1 and Rui Fragoso 2,3,4 1 Faculdade de Ciˆ encias e Tecnologias, Universidade do Algarve, Edif´ ıcio 8, 8005-139 Faro, Portugal 2 Universidade de ´ Evora (UE), Centro de Estudos e Formac ¸˜ ao Avanc ¸ada em Gest˜ ao e Economia Tecnologias, 7000-809 ´ Evora, Portugal 3 Department of Management, Universidade de ´ Evora, 7000-809 ´ Evora, Portugal 4 Instituto de Ciˆ encias Agr´ arias e Ambientais Mediterrˆ aneas, Universidade de ´ Evora, 7000-809 ´ Evora, Portugal Correspondence should be addressed to Ant´ onio Xavier; amxav@sapo.pt Received 30 January 2014; Accepted 2 May 2014; Published 3 June 2014 Academic Editor: Konstantina Skouri Copyright © 2014 Ant´ onio Xavier et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A process of agricultural data disaggregation is developed to address the lack of updated disaggregated data concerning main livestock categories at subregional and county level in the Alentejo Region, southern Portugal. Te model developed considers that the number of livestock units is a function of the agricultural and forest occupation, and data concerning the existing agricultural and forest occupation, as well as the conversion of livestock numbers into normal heads, are needed in order to fnd this relation. Te weight of each livestock class is estimated using a dynamic process based on a generalized maximum entropy model and on a crossentropy minimization model, which comprises two stages. Te model was applied to the county of Castelo de Vide and their results were validated in cross reference to real data from diferent sources. 1. Introduction Disaggregated statistical information is necessary to have a correct analysis of spatial patterns inside each country, but data on agricultural and forest occupation and production are frequently found only at national and subnational level [1–4], and ofentimes this problem does not have an appropriate and accurate solution. In Portugal, southern Europe, apart from the general lack of data on agricultural and forest occupation, there is a need for up-to-date data on livestock numbers [2]. Only the General Agricultural Census (GAC), conducted by the National Institute of Statistics (NIS) every 10 years, features information at disaggregated level by subregion, county, and parish. Te other information sources display information merely according to agrarian regions and NUTS II [5, 6]. Even the diferent agents operating in the territory do not have more detailed data, and only the health veterinary entities have some more accurate data for nowadays, which is not accessible to all. However, planning and devising of a clear and sustain- able rural development policy call for the availability of disaggregated information [4], at least when it comes to the numbers of livestock intended for breeding, mainly in regions where these variables have a great importance for the farmers’ income. Afer the entrance of Portugal into the European Union, the Alentejo region, southern Portugal, has come under the infuence of diferent policies and as a consequence there are several inland rural areas with problems and in decline, as well as the extensifcation of agricultural activities [7]. In this region, the importance of livestock breeding activity is unquestionable [8]. A particular county where there is a tendency towards demographic decrease is Castelo de Vide located in the NUTS II of Alto Alentejo. Several teams from the Uni- versity of ´ Evora have performed depth studies and identi- fed this county as a case study about the decline process of the inland counties of the NUTS II of Alto Alentejo. Here, there is a need for data on extensive livestock for Hindawi Publishing Corporation Advances in Operations Research Volume 2014, Article ID 397675, 9 pages http://dx.doi.org/10.1155/2014/397675