<p><strong>Abstract.</strong> The diversity and heterogeneity of coastal, estuarine and stream habitats has led to them becoming a prevalent topic for study. Woody ruins are areas of potential riverbed habitat, particularly for fish. Therefore, the mapping of those areas is of interest. However, due to the limited visibility in some river systems, satellites, airborne or other camera-based systems (passive systems) cannot be used. By contrast, sidescan sonar is a popular underwater acoustic imaging system that is capable of providing high- resolution monochromatic images of the seafloor and riverbeds. Although the study of sidescan sonar imaging using supervised classification has become a prominent research subject, the use of composite texture features in machine learning classification is still limited. This study describes an investigation of the use of texture analysis and feature extraction on side-scan sonar imagery in two supervised machine learning classifications: Support Vector Machine (SVM) and Decision Tree (DT). A combination of first- order texture and second-order texture is investigated to obtain the most appropriate texture features for the image classification. SVM, using linear and Gaussian kernels along with Decision Tree classifiers, was examined using selected texture features. The results of overall accuracy and kappa coefficient revealed that SVM using a linear kernel leads to a more promising result, with 77% overall accuracy and 0.62 kappa, than SVM using either a Gaussian kernel or Decision Tree (60% and 73% overall accuracy, and 0.39 and 0.59 kappa, respectively). However, this study has demonstrated that SVM using linear and Gaussian kernels as well as a Decision Tree makes it capable of being used in side-scan sonar image classification and riverbed habitat mapping.</p>

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As an archipelagic country, the shipping sector in Indonesia becomes crucial in delivering goods inter-island, and due to increasing transportation demands. However, that industry encounters some challenges of the ocean environment that could lead to vessel accidents. An investigation into the accident is crucial since this is related to the properties, environment, and life disadvantages. The wrecks of sinking vessels also could harm the environment, providing an obstacle to the sea passage hence increasing the risk of a shipping operation. A proper and comprehensive investigation needs to be carried out to identify the factors that contribute to the accident, so then risk mitigation can be taken to prevent re-occurrence. In the case of missing foundered or sunken vessels, an underwater examination is a must, so the investigator understands the real condition of the vessel. Although diver and underwater robotic surveys are still prevalent in the investigation, these techniques have limitations due to visibility and location. By contrast, those limitations can be addressed using hydro-acoustic technologies, which are capable of providing high-resolution underwater images and digital elevation model (DEM) bathymetry. Thus, the use of these technologies is promising in-vessel accident investigation, both in-situ investigation, and post-processing analysis. This paper describes an examination of the use of side-scan sonar and multibeam echosounder in-vessel accident investigation. The use of slope feature and edge-detection technique are also investigated concerning the investigation. Results indicate that those acoustic systems can contribute to the inquiry effectively by portraying some underwater objects as the accident suspects. Besides, slope and edge detection methods also produce expectant outcomes to support underwater object detection and investigation.

Kepulauan Raja Ampat merupakan salah satu tujuan wisata utama di Indonesia dan juga sebagai kawasan konservasi alam. Hal tersebut disebabkan karena wilayah tersebut kaya akan keanekaragaman hayati, kenampakan dan sumber daya alam, serta budaya. Pada tahun 2014, pemerintah Indonesia menyelenggarakan kegiatan Sail Raja Ampat sebagai bagian promosi pembangunan di wilayah tersebut. Badan Pengkajian dan Penerapan Teknologi (BPPT) berperan dalam kegiatan Sail tersebut dengan menggunakan KR Baruna Jaya IV untuk melakukan survei kelautan maupun kegiatan diseminasi teknologi. Penelitian ini bertujuan untuk memberikan gambaran kegiatan survei hidro-oseanografi di perairan Raja Ampat sebagai bagian kegiatan Sail Raja Ampat. Kegiatan survei dilakukan pada dua area utama yaitu Teluk Kabui dan Selat Sagewin. Hasil menunjukkan bahwa survei tersebut mampu memberikan gambaran morfologi di kedua area tersebut. Secara batimetri perairan Teluk Kabui memiliki kedalaman antara 18 – 53 meter, sedangkan kedalaman perairan Selat Sagewin berkisar antara 104  - 508 meter. Rata – rata suhu di perairan Raja Ampat diketahui berkisar antara 28? – 29?C dan memiliki salinitas berkisar antara 32.5 - 35 psu. Litologi berupa batupasir, batugamping, dan lempung juga berhasil diketahui dari survei tersebut. Data – data ilmiah kebumian tersebut bermanfaat untuk melengkapi data – data yang sudah ada ataupun sebagai dasar perencanaan kegiatan penelitian selanjutnya. Disamping itu, data tersebut dapat dimanfaatkan untuk mengetahui karakteristik alam di perairan Raja Ampat sebagai pendukung kegiatan pembangunan di wilayah tersebut.