02 Oct 2018
In this study, the prediction of urban growth was simulated by Artificial NeuralÂ Network (ANN) model using MOLUSCE, plugin of QGIS. Objectives of this study is toÂ illustrate the urban growth in Malang City over time span of 24 years and also to predict theÂ future of urban growth using ANN model for the year 2027. Land cover maps were extracted forÂ 2003, 2009 and 2015 via remote sensing images from Landsat ETM+ and OLI, respectively. TheÂ overall classification accuracy and kappa coefficient for all classified maps were over 85% andÂ 0.76, respectively. According to the simulation result, 1049.58 ha of vegetation and 241.29 haÂ of bare land in 2015 would experience a transition to built-up areas in 2027. Then, the built-upÂ areas would experience an increase by 11.79% from 2015 to 2027. In 2027, the built up areasÂ would covered the city by 73.21% of the city area. There was a trend in increasing of built-upÂ areas during the period 2003 to 2027. Overall, the result shows that urban growth models byÂ using ANN model can be a considerable option for future changes according to past and currentÂ factors.
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