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  3. Juniarto

Analisis Citra Berbasis Objek Pada Bangunan Pantai di Teluk Manado

Chalvin Juniarto(1), Joyce Christian Kumaat(2), Denny Maliangkay(3),


(1) Program Studi Geografi, Fakultas Ilmu Sosial dan Hukum, Universitas Negeri Manado
(2) Program Studi Geografi, Fakultas Ilmu Sosial dan Hukum, Universitas Negeri Manado
(3) Program Studi Geografi, Fakultas Ilmu Sosial dan Hukum, Universitas Negeri Manado
Corresponding Author

Abstract


This research aims to analyze the spatial distribution and characteristics of coastal buildings in Manado Bay using an object-based image analysis approach. The research method used is descriptive-analytical, utilizing 2023 spatial data obtained from Sentinel 2A satellite imagery. The analysis was conducted through segmentation and classification techniques based on Object-Based Image Analysis (OBIA) using eCognition software. The results showed that the OBIA method was able to identify and separate objects based on spectral, shape and texture attributes. The classification of the Manado Bay area, which has an area of 4,217 hectares, shows that this area is dominated by vegetation and open land (1,466 ha), followed by sea water bodies (1,566 ha), built-up land (785 ha), shallow water habitat (386 ha), and other objects (15 ha). The total accuracy of 74.36% through the guided method, explains the effectiveness in identifying the main features in the study area as the optimal approach used in OBIA. The results of this study illustrate the dynamics of the development of Manado Bay coastal area through the distribution pattern and characteristics of the buildings detected. The concentration of built-up land in the central part of the bay reflects the dominance of economic activities, such as trade, industry, services and tourism. On the other hand, the presence of vegetation and open land in the outer area of the bay shows great potential for local economic development, but also faces the threat of land conversion that can affect the balance of coastal ecosystems.

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DOI: 10.36412/jepst.v6i1.3888

DOI (PDF): https://doi.org/10.36412/jepst.v6i1.3888.g1772

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