Object-Based Image Analysis for LULC Change Detection: Impact of Yogyakarta International Airport Development

Abstract:

The construction of Yogyakarta International Airport (YIA), driven by the limitations of land use at the former Adisutjipto Airport, is a key focal point of this research. The development of YIA has led to significant land cover changes in 2016 to 2021, transforming predominantly agricultural and fisheries land into built-up areas. Numerous studies have utilized remote sensing data to analyze land cover and land use (LULC) changes in Kulonprogo Regency, applying a range of remote sensing analytical methods. The most substantial LULC changes have been observed in Temon District, where agricultural land has sharply decreased, coinciding with the expansion of built-up areas. This study aims to further examine land use changes in Temon District, employing object-based classification techniques to enhance the accuracy of land cover analysis. In this study, OBIA classified land cover with 80% accuracy for the 2016 image (scale 100, shape 0.7, compactness 0.7) and 86% for the 2021 image (scale 100, shape 0.9, compactness 0.2). The most significant change was a 537-hectare reduction in paddy field.

• Periodical: Engineering Headway (Volume 27)
• Pages: 685-697
• DOI: https://doi.org/10.4028/p-y0Uq4p
• Online since: October 2025
• Authors: Yana Oktaviana, Abdul Basith*
• Keywords: Change Detection, Classification, Object-Based Image Analysis (OBIA), Segmentation

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