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Risk Screening Environmental Indicators Model Change Based on SpectralTransformation Around New Yogyakarta International Airport

Sidiq Wahid Akhsin Budi Nur, Fariz Trida Ridho, Saputro Purnomo Adi, Sholeh Muh

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 8

143--160

The development of New Yogyakarta International Airport (NYIA) in Temon sub-district is aimed at improving the progress of the surrounding region, where the construction has an impact on the increase in built-up land of 572.38 hectare (2013–2017) and 268.67 hectare (2017–2023) which is potentially a decrease in the environmental quality index. The purpose of the research was to analyze changes in the environmental quality index Risk Screening Environmental Indicators (RSEI) of 2013, 2017 and 2024 around NYIA. The research designs used quantitative approaches with scoring approaches, while research methods used spectral transformation and Principal Component Analysis transformation. The research has limited the use of Landsat 8 image data as a primary data source with a spatial resolution of 30 meters, where the image has not yet been able to deliver the results of the research with a high degree of exhaustion. The originality of the research is the identification of changes in the environmental quality index that are correlated with changes in built-up land and vegetation coverage. The results of the study showed a decrease in the RSEI values, where high-level RSEIs decreased by about 295.17 hectare (2013–2017) and 1720.91 hectare (2017–2024), in addition there was an increase in the area of low-level RSEI by about 122.33 hectare (2013–2017) and 1898.79 hectare (2017–2024). The decline in RSEI in the area study has been correlated with increased built-up land and decreased vegetation area, with built-up land increasing by 572.38 hectare (2013–2017) and 269.97 hectare (2017–2024), besides decreasing vegetation areas by 137.82 hectare (2013–2017), and 97.34 hectare (2017–2024). The study concluded that there was a decrease in the environmental quality index, where increased built-up land and decreased vegetation area were influential factors. This research opens up further research opportunities to predict the environmental quality index with the cellular automata model.

Built-Up Development Prediction Based on Cellular Automata Modelling Around New Yogyakarta International Airport

Sidiq Wahid Akhsin Budi Nur, Fariz Trida Ridho, Saputro Purnomo Adi, Sholeh Muh

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 1

238--250

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.