Effect of Transportation Infrastructure on Built-up Area Using Prediction of Land Use/Cover Change: Case Study of Yogyakarta International Airport, Indonesia


Irwansyah Sukri(1*), Rika Harini(2), Sudrajat Sudrajat(3)

(1) Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
(2) Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
(3) Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
(*) Corresponding Author


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.


remote sensing; land use change; prediction simulation; artificial Neural Network; Effect of Transportation Infrastructure

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DOI: https://doi.org/10.22146/ijg.68216

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