Spatiotemporal analysis and scenario simulation of agricultural land use land cover using GIS and a Markov chain model

• Autor(a) principal: Viana, Cláudia M.
• Data de Publicação: 2018
• Outros Autores: Rocha, Jorge
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/57917
• topic: Agriculture; LULC; Spatiotemporal; CA-Markov; GIS; Beja

In recent decades, the abandonment of agricultural land has been an international trend. In Portugal, the same occurred confirming marked changes in the agricultural landscape. With this study, we intend to identify the major changes that occurred in the agricultural areas of the largest district of Portugal - Beja - that has agriculture as economic background. Particularly, we analysed the spatiotemporal transitions of land with natural propensity or use for agricultural activities (namely, Arable land, Olive groves, Vineyards, Other permanent crops, Pastures and Heterogeneous agricultural areas) and we calculated a transition probability matrix to get a possible future scenario of the main agriculture transitions for the year of 2024, using GIS and the Markov chain model. Data from CORINE land cover for 2000, 2006 and 2012 years were used to evaluate the main changes. The analysis results show that in these 12 years, the land use type of approximately 12.9% of the territory has been changed. Despite the decrease in agricultural areas, they continue to predominate in Beja territory, occupying more than 67% of the total area. It is worth noting that Olive groves crops were the agriculture land type that increased the most between 2000 and 2012 (about 3%). Regarding the future agriculture transitions, we highlight the possible transition nearly of 13.3% among land uses between 2012 and 2024, of which the 10.5% correspond to agricultural areas. The agricultural land type that will undergo major changes is the Other Permanent crops since it has a probability of 39% to transit to other use.