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

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.

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Publication Details

Journal
Engineering headway
Published
2025-10-13
DOI
https://doi.org/10.4028/p-y0uq4p
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Abdul Basith, Yana Oktaviana
Engineering headway
Remote-Sensing Image Classification
article

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

Abdul Basith, Yana Oktaviana
article en

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.

Engineering headwayVol. 27
Universitas Gadjah Mada (ID)
Openalex Percentile: Top 59%
Remote-Sensing Image Classification
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Object-Based Image Analysis for LULC Change Detection: Impact of Yogyakarta International Airport Development — Abdul Basith, Yana Oktaviana · Engineering headway (2025) | TGRS Research Map | TGRS