Wahid Akhsin Budi Nur Sidiq, Trida Ridho Fariz, Purnomo Adi Saputro, Muh Sholeh
New Yogyakarta International Airport (NYIA) in Kulon Progo Regency was developed with the primary objective of fostering economic growth. The initiation of operations at NYIA in March 2020 triggered substantial urban development in the surrounding area. This research aimed to monitor the changes in land cover and predict the development of urban areas. The research methodology comprised the use of Random Forest, Classification, and Regression Tree machine learning algorithms to create land cover maps. It also incorporated Cellular Automata (CA), which was used to make prediction related to land development. The results showed that the land cover map had an overall accuracy level of above 0.80. Furthermore, it was observed from the results of the time series land cover analysis that there was a rapid growth in built-up lands. Between 2013 and 2017, these lands expanded by 572.38 hectares and further increased by 268.97 hectares from 2017 to 2023, leading to the conversion of 571.64 hectares of agricultural lands. On the basis of these findings, it was projected that by 2033, there would be an expansion of 386.08 hectares in built-up lands, with approximately 356.82 hectares converted from agricultural areas. The accuracy assessment of the 2023 land cover prediction map showed a high level of correctness, with a 97% accuracy rate. On the basis of these results, it was concluded that land conversion is essential to prevent environmental degradation, and further research can be carried out with the aim of assessing environmental quality indices. © 2024, Polskie Towarzystwo Inzynierii Ekologicznej (PTIE). All rights reserved.
Geography Departement, Faculty of Social Sciences and Political Science, Universitas Negeri Semarang, Sekaran, Semarang City, 50229, Indonesia; Environmental Science Department, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang, Sekaran, Semarang City, 50229, Indonesia
