In Malaysia, areas under oil palm plantations have increased dramatically since the early twentieth century and have resulted in multiple conversions of land change. This paper presents a spatial and temporal model for simulation of oil palm expansion in the Kuala Langat district, Malaysia. The model is an integration of cellular automata (CA), multicriteria evaluation (MCE), and Markov chain (MC) analysis while MCE provides transition rules of CA iterations and MC analysis assigns a transition probability to each single pixel at the time steps. Evaluation criteria consist of constraints and nine suitability factors indicating environmental and socioeconomic issues of oil palm development. In the first simulation, changes of six land-cover classes were projected to the year 2008 based on transitions between 1997 and 2002. Two measures of quantity disagreement and allocation disagreement were adopted to validate model outcome. The simulation of land-cover change of the year 2020 was done based on the transition observed between 1997 and 2002 regarding the satisfactory agreement of the projection and the reference data at the first simulation. The results, based on five landscape metrics, indicated continuous spatial patterns of oil palm plantations but more fragmented spatial patterns of other land classes by the year 2020.

Analyzing the effects of urban development on dynamic and spatial patterns of land use is vital to establish more efficient land management policies. However, in Malaysia, such effects are usually explained without quantitative metrics. This research quantified the future impact of urban expansion on the dynamic of land use by developing the area-independent dynamic metric. The metric was calculated based on summarizing the cross tabulation matrices of change in an urbanizing area at west coast of Peninsular Malaysia. Another two land use measures involving vulnerability to gain and Appl. Spatial Analysis vulnerability to loss were used to evaluate tendency of land classes to transition. The effects of urban development on spatial patterns of land use were quantified using two landscape metrics involving the Edge Density (ED) and Area-Weighted Mean Patch Fractal Dimension (AWMPFD). Analyses were carried out on a set of spatial land use data including observed 1997, 2002, and 2008, as well as a simulated near future land change for the year 2020 under a spatio-temporal land use model. Results showed that urban development practices would influence the dynamic of land transition in the near future. Urban growth would experience a fast-growing dynamic and high vulnerability to gain than loss while the dynamic and vulnerability of forest/wetland covers would decrease in terms of loss. Moreover, agriculture practices tend to be hindered by further urban development in the coming years. Another important finding was that urban development process would influence the spatial patterns of land use in the near future.

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