Identifikasi Permukiman Kumuh Menggunakan Citraunmanned Aerial Vehicle (UAV) di Kecamatan Medan Belawan, Kota Medan

Abstract

This research aims to identify and map slum settlements in the coastal area of Medan Belawan, Medan City, utilizing a combination of remote sensing technologies. The methodology involved Unmanned Aerial Vehicle (UAV) aerial photo acquisition, which generated an ultra-high-resolution orthomosaic map (2.90 cm/pixel) covering an area of 62.60 Ha. This data was subsequently analyzed using Object-Based Image Analysis (OBIA), an advanced image analysis technique that classifies objects based on spectral, spatial, and elevation attributes. The identification and classification processes were directly validated through field observations to ensure accuracy. The results of land cover classification using OBIA identified slum settlements covering 9.51 Ha, approximately 18.6% of the total analyzed settlement area. Further building height analysis revealed that the majority of structures were low-rise buildings (<6 meters), constituting 92.7% of all buildings, reflecting the characteristics of dense settlements in coastal areas prone to tidal flooding and experiencing poor drainage. The physical characteristics of slum settlements identified through image analysis—such as high building density, irregular patterns, low heights, and frequently inundated locations—were highly consistent with actual field conditions. This study demonstrates the effectiveness of integrating UAV and OBIA technologies in accurately identifying and mapping slum settlements, even in difficult-to-access coastal regions. Although this method has limitations in directly identifying socioeconomic aspects of slum conditions, the resulting physical spatial data are highly precise. These findings are expected to provide a strong scientific basis for spatial planning, prioritizing interventions, and implementing more targeted settlement quality improvement programs in Medan Belawan.