Understanding the characteristics of agricultural expansion, particularly oil palm, is important to study its impact on the world’s land. Land use modelling is a tool that can be used to help to understand the key process of oil palm expansion, to assess the current state, the drivers, the processes and the impact of oil palm expansion. Using spatial datasets from different sources, this research models the process of land use change using IDRISI Land Change Modeller to understand the follow up oil palm land use after deforestation events in Indonesia, as well as to predict where the deforestation is likely to occur due to the process of oil palm expansions. Artificial Neural Network method was used to build sub-models during the observation period for the year of 2000 – 2006, while Markov Chain Method was used to predict future land use in 2009.
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Ano de publicação
2015
Autores
Idioma
English
Palavras-chave
deforestation, oil palms, remote sensing, land use, remote sensing, models
Geográfico
Indonesia
