Object-Based Image Analysis for LULC Change Detection: Impact of Yogyakarta International Airport Development
Year: 2025
Type: conference-paper
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.
Source: Engineering headway
DOI: 10.4028/p-y0uq4p
Authors: Yana Oktaviana, Abdul Basith
Institution: Universitas Gadjah Mada
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4415117274