<![CDATA[Subsea pipelines are critical in supporting offshore oil and gas activities, yet they are vulnerable to hazards such as leaks caused by navigation activities. Regular monitoring is essential to reduce associated risks, and multibeam echosounder (MBES) data offer a promising solution for identifying subsea infrastructure. This research presents an object-based interpretation approach for detecting subsea pipelines using MBES data, incorporating interpretation elements such as tone and color, texture, shape, pattern, size, shadow, and site. The research was conducted in the Bawean Sea, East Java, using raw MBES data, vessel offsets, patch test calibration, a sound velocity profiler (SVP), and tidal data. The seafloor topography in the study area is generally flat, ranging from 52.5 to 60.2 meters in depth. Six subsea pipeline objects were identified based on their linear pattern, shallow placement, consistent shape, and spatial context. However, the absence of visible shadow elements—possibly due to sonar resolution, depth, or beam angle limitations—represents a methodological constraint. The study points out the advantages of MBES data combined with object interpretation criteria for non-invasive and efficient subsea pipeline monitoring.]]>
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