Abstract
The development of transportation infrastructure increases the pressure on natural resources, one of which is the increase in the built-up area. The changes do not only happen during the construction of transportation infrastructure but also after its completion. Therefore, this study aims to identify and simulate land use/cover changes in Kulon Progo Regency, Indonesia, to predict the effect of the construction of Yogyakarta International Airport (YIA). A quantitative descriptive method was used with the main data of multitemporal Landsat remote sensing images. Furthermore, the integration of Cellular Automata and Artificial Neural Networks (CA-ANN) was applied to simulate land use/cover change predictions (2035). The results of image classification using the supervised maximum likelihood classification showed an overall accuracy of 85.33% and 86.67% for 2011, and 2015 with 2019 using Landsat 7 and 8 images, respectively. Meanwhile, there was an increase in paddy fields of 1,210.1 ha (2.11%) and built-up area by 2,708.6 ha (4.72%) during 2011 – 2019. Conversely, shrubs and dryland agriculture decreased by 1,594.1 ha (2.78%) and 2,174.1 ha (3.79%). The simulation results indicate that the development of transportation infrastructure further triggers the increase in built-up area, especially around the YIA. Therefore, policymakers and development implementers should adopt and implement appropriate and effective planning for sustainable land use.
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