Integrasi Random Forest dan Landscape Expansion Index LEI untuk Identifikasi Pola Perkembangan Perkotaan Yogyakarta

Abstract

The urban areas of Yogyakarta and its surroundings have experienced highly dynamic growth Therefore research is needed to analyze urban development starting with land cover and land use analysis using Landsat TM and Landsat 8 OLI imagery Random Forest RF classification a machine learning based method was employed to accelerate the land cover and land use classification process This study combines the Random Forest and Landscape Expansion Index LEI methods to analyze land use changes and urban growth patterns LEI was utilized to identify urban development types such as outlying diffusion edge expansion and infilling The study highlights the roles of RF and Google Earth Engine GEE in land cover and land use classification The results show that Yogyakarta and its surrounding urban areas are predominantly expanding outward following an edge expansion pattern especially toward Sleman and Bantul regencies Additionally infilling growth is observed in Gondomanan and Gondokusuman sub districts which are already densely populated areas Outlying development patterns were found in Sleman and Bantul regencies occurring far from the Yogyakarta city center This study underscores that the combination of RF GEE and LEI is an effective method for analyzing urban growth patterns < em>< p>