Perkembangan Pemanfaatan Geographic Information System (GIS) dalam Maritime Surveillance: Analisis Bibliometrik dan Systematic Literature Review

Aridha Ulul Azmi Pakukuh; Steven Toar Sambouw; Asep Suryana; Nefra Firdaus; Harri Dolli Hutabarat; Yuniar Yuniar; Lukman Yudho Prakoso

PDF.

Published: 2026-07-14

Keywords:

Bibliometric Analysis, Geographic Information System, Maritime surveillance, Remote Sensing, Systematic Literature Review, VOSviewer

Aridha Ulul Azmi Pakukuh

Universitas Pertahanan

Steven Toar Sambouw

Indonesia Defense University

Asep Suryana

Indonesia Defense University

Nefra Firdaus

Indonesia Defense University

Harri Dolli Hutabarat

Indonesia Defense University

Yuniar

Indonesia Defense University

Lukman Yudho Prakoso

Indonesia Defense University

Abstract

Perkembangan teknologi geospasial telah mendorong pemanfaatan Geographic Information System (GIS) sebagai salah satu teknologi utama dalam mendukung maritime surveillance. Namun demikian, penelitian mengenai GIS dalam domain maritim masih berkembang secara terfragmentasi sehingga belum tersedia pemetaan yang komprehensif mengenai struktur intelektual, tren penelitian, serta arah pengembangannya. Penelitian ini bertujuan memetakan perkembangan penelitian GIS dalam maritime surveillance melalui pendekatan Systematic Literature Review (SLR) yang dipadukan dengan bibliometric analysis. Proses seleksi literatur mengikuti pedoman PRISMA 2020 terhadap artikel yang diperoleh dari basis data Scopus periode 2016–2026. Dari 370 artikel yang teridentifikasi, sebanyak 99 artikel memenuhi kriteria inklusi dan dianalisis menggunakan VOSviewer melalui network, overlay, dan density visualization, kemudian disintesis menggunakan content analysis. Hasil penelitian menunjukkan bahwa Geographic Information System merupakan tema sentral yang memiliki keterhubungan paling kuat dengan Remote Sensing, Oil Spill, Monitoring, Coastal Management, dan Risk Assessment. Analisis temporal menunjukkan pergeseran penelitian dari pemetaan wilayah pesisir menuju pemanfaatan penginderaan jauh, kemudian berkembang ke penerapan Artificial Intelligence, Machine Learning, dan Deep Learning sebagai pendekatan analitik baru. Content analysis mengidentifikasi enam tema utama penelitian, dengan dominasi kajian mengenai Coastal Management dan Oil Spill Monitoring, sedangkan integrasi kecerdasan buatan masih relatif terbatas. Sintesis hasil penelitian menunjukkan bahwa perkembangan GIS dalam maritime surveillance berlangsung melalui tiga fase, yaitu pemetaan wilayah pesisir, integrasi GIS dan Remote Sensing, serta integrasi GIS dan Artificial Intelligence. Temuan ini menunjukkan bahwa peluang penelitian selanjutnya terletak pada pengembangan sistem maritime surveillance yang lebih adaptif melalui integrasi GIS dengan teknologi analitik cerdas dan sistem pendukung keputusan berbasis data.

Issue

Vol. 1 No. 2 (2026): SISTEM DIGITAL KEAMANAN MARITIM

Section

Articles

How to Cite

Perkembangan Pemanfaatan Geographic Information System (GIS) dalam Maritime Surveillance: Analisis Bibliometrik dan Systematic Literature Review. (2026). Journal Keamanan Dan Keselamatan Maritim, 1(2), 320-358. https://www.fkn.unhan.org/jkkm/article/view/164

References

Aattan, S. A. A., & Al-Bakri, M. (2020). Development of Bridges Maintenance Management System based on Geographic Information System Techniques (Case study: Al-Muthanna Iraq). Journal of Engineering. https://doi.org/10.31026/j.eng.2020.09.09

Agrawal, N., Verma, K., & Kumar, T. (2021). Multicriteria Spatial Decision Support System for Soil Fertility Assessment in Agriculture. International Journal of Computer Applications. https://doi.org/10.5120/ijca2021920975

Agyekum, H., Ali, K.-D., Bueger, C., & Larsen, S. (2024). Maritime security and the inter-agency challenge: The case of Ghana. African Security Review, 33, 353–370. https://doi.org/10.1080/10246029.2024.2314467

Akhtar, M. J., Azhar, M., Khan, N., & Rahman, M. N. (2023). Conceptualizing social media analytics in digital economy: An evidence from bibliometric analysis. Journal of Digital Economy. https://doi.org/10.1016/j.jdec.2023.03.004

Alexandre, C., Devillers, R., Mouillot, D., Seguin, R., & Catry, T. (2024). Ship Detection With SAR C-Band Satellite Images: A Systematic Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 14353–14367. https://doi.org/10.1109/jstars.2024.3437187

Amiri, A. M., Kushwaha, B., & Singh, R. (2023). Visualisation of global research trends and future research directions of digital marketing in small and medium enterprises using bibliometric analysis. Journal of Small Business and Enterprise Development. https://doi.org/10.1108/jsbed-04-2022-0206

Andriulo, F. C., Fiore, M., Mongiello, M., Traversa, E., & Zizzo, V. (2024). Edge Computing and Cloud Computing for Internet of Things: A Review. Informatics, 11, 71. https://doi.org/10.3390/informatics11040071

Anuja, R., & Annrose, J. (2025). End-to-end deep learning for smart maritime threat detection: an AE–CNN–LSTM-based approach. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-19450-4

Apostolopoulos, D. N., & Nikolakopoulos, K. (2021). A review and meta-analysis of remote sensing data, GIS methods, materials and indices used for monitoring the coastline evolution over the last twenty years. European Journal of Remote Sensing, 54, 240 - 265. https://doi.org/10.1080/22797254.2021.1904293

Ardern, C., Büttner, F., Andrade, R., Weir, A., Ashe, M., Holden, S., Impellizzeri, F., Delahunt, E., Dijkstra, H., Mathieson, S., Rathleff, M., Reurink, G., Sherrington, C., Stamatakis, E., Vicenzino, B., Whittaker, J. L., Wright, A., Clarke, M., Moher, D., . . . Winters, M. (2021). Implementing the 27 PRISMA 2020 Statement items for systematic reviews in the sport and exercise medicine, musculoskeletal rehabilitation and sports science fields: the PERSiST (implementing Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science) guidance. British Journal of Sports Medicine, 56, 175 - 195. https://doi.org/10.1136/bjsports-2021-103987

Asif, Z., Chen, Z., An, C., & Dong, J. (2022). Environmental Impacts and Challenges Associated with Oil Spills on Shorelines. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse10060762

Ba, H., Zhang, L., He, X., & Li, S. (2025). Knowledge Mapping and Global Trends in Simulation in Medical Education: Bibliometric and Visual Analysis. JMIR Medical Education, 11. https://doi.org/10.2196/71844

Bae, I., & Hong, J. (2023). Survey on the Developments of Unmanned Marine Vehicles: Intelligence and Cooperation. Sensors (Basel, Switzerland), 23. https://doi.org/10.3390/s23104643

Baghdady, S. M., & Abdelsalam, A. A. (2024). Ten years of oil pollution detection in the Eastern Mediterranean shipping lanes opposite the Egyptian coast using remote sensing techniques. Scientific Reports, 14. https://doi.org/10.1038/s41598-024-67983-x

Bakirci, M. (2024). Advanced Ship Detection and Ocean Monitoring with Satellite Imagery and Deep Learning for Marine Science Applications. Regional Studies in Marine Science. https://doi.org/10.1016/j.rsma.2024.103975

Balogun, A., Yekeen, S., Pradhan, B., & Yusof, W. K. (2020). Oil spill trajectory modelling and environmental vulnerability mapping using GNOME model and GIS.. Environmental pollution, 115812 . https://doi.org/10.1016/j.envpol.2020.115812

Balogun, A., Yekeen, S., Pradhan, B., & Yusof, W. K. (2020). Oil spill trajectory modelling and environmental vulnerability mapping using GNOME model and GIS. Environmental Pollution, 115812. https://doi.org/10.1016/j.envpol.2020.115812

Barros, R. P., Fajardo, A., & Lara-Borrero, J. (2025). Decentralized Renewable-Energy Desalination: Emerging Trends and Global Research Frontiers—A Comprehensive Bibliometric Review. Water. https://doi.org/10.3390/w17142054

Bernabé, P., Gotlieb, A., Legeard, B., Marijan, D., Sem-Jacobsen, F., & Spieker, H. (2023). Detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning. IEEE Transactions on Intelligent Transportation Systems, 25, 1166-1177. https://doi.org/10.1109/tits.2023.3322690

Boloy, R., Da Cunha Reis, A., Rios, E. M., De Araújo Santos Martins, J., Soares, L., De Sá Machado, V. A., & De Moraes, D. R. (2021). Waste-to-Energy Technologies Towards Circular Economy: a Systematic Literature Review and Bibliometric Analysis. Water, Air, & Soil Pollution, 232, 1-25. https://doi.org/10.1007/s11270-021-05224-x

Bosso, L., Saviano, S., Abagnale, M., Bellardini, D., Bolinesi, F., Botte, V., Buondonno, A., Carotenuto, Y., Casotti, R., Chiusano, M., Cipolletta, F., Conversano, F., De Domenico, F., Del Gaizo, G., Donnarumma, V., Furia, M., Iudicone, D., Kokoszka, F., Laface, F., . . . D’Alelio, D. (2025). GIS-based integration of marine data for assessment and management of a highly anthropized coastal area. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-00206-z

Brennan, S., & Munn, Z. (2021). PRISMA 2020: a reporting guideline for the next generation of systematic reviews.. JBI evidence synthesis, 19 5, 906-908 . https://doi.org/10.11124/jbies-21-00112

Bueger, C., & Stockbruegger, J. (2022). Maritime security and the Western Indian Ocean’s militarisation dilemma. African Security Review, 31, 195 - 210. https://doi.org/10.1080/10246029.2022.2053556

Buri, Z., & Kiss, J. T. (2025). Digitalisation in the Context of Industry 4.0 and Industry 5.0: A Bibliometric Literature Review and Visualisation. Applied System Innovation. https://doi.org/10.3390/asi8050137

Carpenter-Kling, T., Truter, H., Lemahieu, A., Snow, B., Strand, M., Rivers, N., Nupnau, L., & Lombard, A. T. (2025). Scenario planning from the bottom up: supporting inclusive and ecosystem-based approaches to marine spatial planning. npj Ocean Sustainability, 4. https://doi.org/10.1038/s44183-025-00140-7

Cavalli, R. (2024). Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review. Remote. Sens., 16, 446. https://doi.org/10.3390/rs16030446

Chaal, M., Ren, X., Bahootoroody, A., Basnet, S., Bolbot, V., Banda, O. V., & Van Gelder, P. (2023). Research on risk, safety, and reliability of autonomous ships: A bibliometric review. Safety Science. https://doi.org/10.1016/j.ssci.2023.106256

Chainando, N., Martawidjaja, M., Darius, R. A., Yahya, L. C., Yemima, S., Tan, W. S., Harito, C., Chandra, R. C., Andhini, G. K., Putra, K. B., Tobing, C. C. L., Syafi’i, M., & Syafrudin, M. (2025). Applying 3D Scanning and Printing Techniques to Produce Upper Limb Prostheses: Bibliometric Analysis and Scoping Review. Prosthesis. https://doi.org/10.3390/prosthesis7020026

Chang, C.-H., Kontovas, C. A., Yu, Q., & Yang, Z. (2021). Risk assessment of the operations of maritime autonomous surface ships. Reliab. Eng. Syst. Saf., 207, 107324. https://doi.org/10.1016/j.ress.2020.107324

Chipunza, T., & Ntsalaze, L. (2025). Multi-dimensional poverty: a bibliometric analysis and content co-occurrence literature review. Humanities and Social Sciences Communications, 12. https://doi.org/10.1057/s41599-025-04924-7

Christofi, D., Mettas, C., Evagorou, E., Stylianou, N., Eliades, M., Theocharidis, C., Chatzipavlis, A. E., Hasiotis, T., & Hadjimitsis, D. (2025). A Review of Open Remote Sensing Data with GIS, AI, and UAV Support for Shoreline Detection and Coastal Erosion Monitoring. Applied Sciences. https://doi.org/10.3390/app15094771

Couto, J., & Baltazar, M. E. (2025). Sustainable Airport Development: A Literature Review Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses Methodology, Using OpenAlex Database. Sustainability. https://doi.org/10.3390/su17094184

De Magalhães, M. E., Barbosa, C. E., Cordeiro, K. F., Isidorio, D., & Souza, J. (2023). Improving Maritime Domain Awareness in Brazil through Computer Vision Technology. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse11071272

Dike, E., Oyetunji, A., & Amaechi, C. (2023). Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse11081528

Dima, A., Zamfir, A., Dobrin, C., Triculescu, M., Mișu, S., & Pantelimon, A. D. (2026). Women's Leadership as a Driver of Small and Medium‐Sized Enterprises Sustainability and Green Transition: A Bibliometric and Systematic Review. Corporate Social Responsibility and Environmental Management. https://doi.org/10.1002/csr.70756

Ding, G., Liu, J., Li, D., Fu, X., Zhou, Y., Zhang, M., Li, W., Wang, Y., Li, C., & Geng, X. (2025). A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse13010082

Dong, J., Liang, X., Du, B., Ju, Y., Wang, Y., & Guo, H. (2025). Applications of Geographic Information Systems in Ecological Impact Assessment: A Methods Landscape, Practical Bottlenecks, and Future Pathways. Sustainability. https://doi.org/10.3390/su172210358

Dong, P., Liu, J., Tao, H., Zhao, Y., Feng, Z., & Luo, H. (2025). Long-Endurance Collaborative Search and Rescue Based on Maritime Unmanned Systems and Deep-Reinforcement Learning. Sensors (Basel, Switzerland), 25. https://doi.org/10.3390/s25134025

Dritsas, E., & Trigka, M. (2025). Remote Sensing and Geospatial Analysis in the Big Data Era: A Survey. Remote Sensing. https://doi.org/10.3390/rs17030550

Du, Q., Zhao, R., Wan, Q., Li, S., Li, H., Wang, D., Ho, C. W., Dai, Z., Chen, Y., & Shan, D. (2024). Protocol for conducting bibliometric analysis in biomedicine and related research using CiteSpace and VOSviewer software. STAR Protocols, 5. https://doi.org/10.1016/j.xpro.2024.103269

Dupont, C., Gourmelon, F., Meur-Férec, C., Herpers, F., & Visage, C. L. (2020). Exploring uses of maritime surveillance data for marine spatial planning: A review of scientific literature. Marine Policy, 117, 103930. https://doi.org/10.1016/j.marpol.2020.103930

Durlik, I., Miller, T., Cembrowska-Lech, D., Krzemińska, A., Złoczowska, E., & Nowak, A. (2023). Navigating the Sea of Data: A Comprehensive Review on Data Analysis in Maritime IoT Applications. Applied Sciences. https://doi.org/10.3390/app13179742

Edwards, S. (2022). Fragmentation, Complexity and Cooperation: Understanding Southeast Asia's Maritime Security Governance. Contemporary Southeast Asia: A Journal of International and Strategic Affairs, 44, 121 - 87. https://doi.org/10.1355/cs44-1d

El-Magd, I., Zakzouk, M., Ali, E., & Abdulaziz, A. M. (2021). An Open Source Approach for Near-Real Time Mapping of Oil Spills along the Mediterranean Coast of Egypt. Remote. Sens., 13, 2733. https://doi.org/10.3390/rs13142733

Elsman, E., Mokkink, L., Terwee, C., Beaton, D., Gagnier, J. J., Tricco, A. C., Baba, A., Butcher, N. J., Smith, M., Hofstetter, C., Aiyegbusi, O., Berardi, A., Farmer, J., Haywood, K. L., Krause, K., Markham, S., Mayo-Wilson, E., Mehdipour, A., Ricketts, J., . . . Offringa, M. (2024). Guideline for reporting systematic reviews of outcome measurement instruments (OMIs): PRISMA-COSMIN for OMIs 2024. Health and Quality of Life Outcomes, 22. https://doi.org/10.1186/s12955-024-02256-9

Escandón-Panchana, J., Vallejo, R. E., Escandón-Panchana, P., Velástegui-Montoya, A., & Herrera-Franco, G. (2022). Spatial Planning of the Coastal Marine Socioecological System—Case Study: Punta Carnero, Ecuador. Resources. https://doi.org/10.3390/resources11080074

Ezzeddini, L., Ktari, J., Frikha, T., Alsharabi, N., Alayba, A., Alzahrani, A. J., Jadi, A., Alkholidi, A., & Hamam, H. (2024). Analysis of the performance of Faster R-CNN and YOLOv8 in detecting fishing vessels and fishes in real time. PeerJ Computer Science, 10. https://doi.org/10.7717/peerj-cs.2033

Forti, N., d’Afflisio, E., Braca, P., Millefiori, L. M., Carniel, S., & Willett, P. (2022). Next-Gen Intelligent Situational Awareness Systems for Maritime Surveillance and Autonomous Navigation [Point of View]. Proc. IEEE, 110, 1532-1537. https://doi.org/10.1109/jproc.2022.3194445

Franchi, F., Graziosi, F., Di Fina, E., & Galassi, A. (2024). A Survey of Cloud-Enabled GIS Solutions Toward Edge Computing: Challenges and Perspectives. IEEE Open Journal of the Communications Society, 5, 312-331. https://doi.org/10.1109/ojcoms.2023.3344198

Freire, W. P., Melo, W. S., Nascimento, V. D. D., Nascimento, P. R. M., & De Sá, A. O. (2022). Towards a Secure and Scalable Maritime Monitoring System Using Blockchain and Low-Cost IoT Technology. Sensors (Basel, Switzerland), 22. https://doi.org/10.3390/s22134895

Gaadha, B., & Umasankar, M. (2026). A systematic literature review on non-familial financial socialization. Discover Psychology. https://doi.org/10.1007/s44202-026-00640-8

Gamage, C., Dinalankara, R., Samarabandu, J., & Subasinghe, A. (2023). A comprehensive survey on the applications of machine learning techniques on maritime surveillance to detect abnormal maritime vessel behaviors. WMU Journal of Maritime Affairs, 22, 447 - 477. https://doi.org/10.1007/s13437-023-00312-7

Gao, Z., Li, Y., Shao, Y., Tao, F., Wang, Z., & Chen, G. (2026). HPRT-YOLO: Enhanced lightweight UAV maritime search and rescue model based on YOLOv11n. iScience, 29. https://doi.org/10.1016/j.isci.2026.115366

Garcia, L. P., Furano, G., Ghiglione, M., Zancan, V., Imbembo, E., Ilioudis, C., Clemente, C., & Trucco, P. (2024). Advancements in Onboard Processing of Synthetic Aperture Radar (SAR) Data: Enhancing Efficiency and Real-Time Capabilities. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 16625-16645. https://doi.org/10.1109/jstars.2024.3406155

Guardia, M. (2025). 3D Urban Digital Twinning on the Web with Low-Cost Technology: 3D Geospatial Data and IoT Integration for Wellness Monitoring. Big Data Cogn. Comput., 9, 107. https://doi.org/10.3390/bdcc9040107

Guo, Y., Liu, R. W., Qu, J., Lu, Y., Zhu, F., & Lv, Y. (2023). Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways. IEEE Transactions on Intelligent Transportation Systems, 24, 12779-12792. https://doi.org/10.1109/tits.2023.3285415

Gupta, H., Verma, O. P., Sharma, T., Varshney, H., Agarwal, S., & Pak, W. (2024). Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery. Scientific Reports, 14. https://doi.org/10.1038/s41598-024-80239-y

Han, W., Wang, T., He, Z., Wang, C., Hui, Z., Lei, S., Hao, N., Li, N., & Wang, X. (2025). Global research trends on gastrointestinal cancer and mental health (2004–2024): a bibliographic study. Frontiers in Medicine, 12. https://doi.org/10.3389/fmed.2025.1515853

Han, X., Armenakis, C., & Jadidi, M. (2021). Modeling Vessel Behaviours by Clustering AIS Data Using Optimized DBSCAN. Sustainability. https://doi.org/10.3390/su13158162

Haque, T., Syed, M. A. B., Das, S., & Ahmed, I. (2024). Advancing Marine Surveillance: A Hybrid Approach of Physics-Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse12111913

Huang, I.-L., Lee, M.-C., Chang, L., & Huang, J.-C. (2024). Development and Application of an Advanced Automatic Identification System (AIS)-Based Ship Trajectory Extraction Framework for Maritime Traffic Analysis. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse12091672

Huang, Y., Liu, W., Lin, Y., Kang, J., Zhu, F., & Wang, F. (2025). FLCSDet: Federated Learning-Driven Cross-Spatial Vessel Detection for Maritime Surveillance With Privacy Preservation. IEEE Transactions on Intelligent Transportation Systems, 26, 1177-1192. https://doi.org/10.1109/tits.2024.3488497

Huo, Y., Dong, X., & Beatty, S. (2020). Cellular Communications in Ocean Waves for Maritime Internet of Things. IEEE Internet of Things Journal, 7, 9965-9979. https://doi.org/10.1109/jiot.2020.2988634

Husaeni, D. F. A., & Nandiyanto, A. (2021). Bibliometric Using Vosviewer with Publish or Perish (using Google Scholar data): From Step-by-step Processing for Users to the Practical Examples in the Analysis of Digital Learning Articles in Pre and Post Covid-19 Pandemic. ASEAN Journal of Science and Engineering. https://doi.org/10.17509/ajse.v2i1.37368

Isbaex, C., Costa, F. D. R. F., & Batista, T. (2025). Application of GIS in the Maritime-Port Sector: A Systematic Review. Sustainability. https://doi.org/10.3390/su17083386

Jahanbakht, M., Xiang, W., Hanzo, L., & Azghadi, M. R. (2020). Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey. IEEE Communications Surveys & Tutorials, 23, 904-956. https://doi.org/10.1109/comst.2021.3053118

Jelokhani‐Niaraki, M., Moradi-Pour, S., Samany, N., & Mohammadkhan, S. (2023). A multiple models-multiple users group GIS-based decision support system for land use problems. Land Use Policy. https://doi.org/10.1016/j.landusepol.2023.106916

Jung, S., Jeong, S., Kang, J., & Kang, J. (2023). Marine IoT Systems With Space–Air–Sea Integrated Networks: Hybrid LEO and UAV Edge Computing. IEEE Internet of Things Journal, 10, 20498-20510. https://doi.org/10.1109/jiot.2023.3287196

Karst, J., McGurrin, R., Gavin, K. E., Luttrell, J., Rippy, W., Coniglione, R., McKenna, J. R., & Riedel, R. (2025). Enhancing Maritime Domain Awareness Through AI-Enabled Acoustic Buoys for Real-Time Detection and Tracking of Fast-Moving Vessels. Sensors (Basel, Switzerland), 25. https://doi.org/10.3390/s25061930

Kelly, C., Ellis, G., & Flannery, W. (2018). Conceptualising change in marine governance: Learning from Transition Management. Marine Policy. https://doi.org/10.1016/j.marpol.2018.06.023

Kim, M., Park, J., & Hyun, C.-U. (2026). A Review of Oil Spill Detection and Monitoring Techniques Using Satellite Remote Sensing Data and the Google Earth Engine Platform. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse14060565

Kim, Y., Kim, J., Lee, W., Park, H., & Cho, D. (2025). FURIOUS: Fully unified risk-assessment with interactive operational user system for vessels. PLOS One, 20. https://doi.org/10.1371/journal.pone.0323300

Kiran, M., Xie, Y., Anjum, N., Ball, G., Pierscionek, B., & Russell, D. (2025). Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1557467

Klarin, A. (2024). How to conduct a bibliometric content analysis: Guidelines and contributions of content co-occurrence or co-word literature reviews. International Journal of Consumer Studies. https://doi.org/10.1111/ijcs.13031

Klarin, A. (2024). How to conduct a bibliometric content analysis: Guidelines and contributions of content co‐occurrence or co‐word literature reviews. International Journal of Consumer Studies. https://doi.org/10.1111/ijcs.13031

Koldasbayeva, D., Tregubova, P., Gasanov, M., Zaytsev, A., Petrovskaia, A., & Burnaev, E. (2024). Challenges in data-driven geospatial modeling for environmental research and practice. Nature Communications, 15. https://doi.org/10.1038/s41467-024-55240-8

Krishnamoorthy, R., Tanaka, K., & Begum, M. (2025). Integrating GIS-Remote Sensing: A Comprehensive Approach to Predict Oceanographic Health and Coastal Dynamics. Remote Sensing in Earth Systems Sciences, 8, 200 - 212. https://doi.org/10.1007/s41976-024-00185-1

Krishnamoorthy, R., Tanaka, K., & Begum, M. (2025). Integrating GIS-Remote Sensing: A Comprehensive Approach to Predict Oceanographic Health and Coastal Dynamics. Remote Sensing in Earth Systems Sciences, 8, 200–212. https://doi.org/10.1007/s41976-024-00185-1

Kuo, C., & Chou, H. (2023). An ontology-based framework for semantic geographic information systems development and understanding. Comput. Geosci., 181, 105462. https://doi.org/10.1016/j.cageo.2023.105462

Kuzior, A., & Sira, M. (2022). A Bibliometric Analysis of Blockchain Technology Research Using VOSviewer. Sustainability. https://doi.org/10.3390/su14138206

Lee, D., Jang, D., & Yoo, S. (2025). Development of a Multidimensional Analysis and Integrated Visualization Method for Maritime Traffic Behaviors Using DBSCAN-Based Dynamic Clustering. Applied Sciences. https://doi.org/10.3390/app15020529

Lester, S., Dubel, A. K., Hernán, G., McHenry, J., & Rassweiler, A. (2020). Spatial Planning Principles for Marine Ecosystem Restoration. https://doi.org/10.3389/fmars.2020.00328

Li, H., Çelik, C., Bashir, M., Zou, L., & Yang, Z. (2024). Incorporation of a global perspective into data-driven analysis of maritime collision accident risk. Reliab. Eng. Syst. Saf., 249, 110187. https://doi.org/10.1016/j.ress.2024.110187

Li, H., Jiao, H., & Yang, Z. (2023). AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods. Transportation Research Part E: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2023.103152

Li, J., Zhang, G., Jiang, C., & Zhang, W. (2023). A survey of maritime unmanned search system: Theory, applications and future directions. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2023.115359

Li, M., Mou, J., Liu, R., Chen, P., Dong, Z., & He, Y. (2019). Relational Model of Accidents and Vessel Traffic Using AIS Data and GIS: A Case Study of the Western Port of Shenzhen City. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse7060163

Li, W., Cheng, K., Shi, G., Desrosiers, R., & Wang, X. (2025). Ship domain models: Reviewing the advancements and exploring the future directions in the maritime autonomous surface ships. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2025.120935

Li, X., Yue, J., Wang, S., Luo, Y., Su, C., Zhou, J., Xu, D., & Lu, H. (2023). Development of Geographic Information System Architecture Feature Analysis and Evolution Trend Research. Sustainability. https://doi.org/10.3390/su16010137

Li, Z., Ning, H., Gao, S., Janowicz, K., Li, W., Arundel, S., Yang, C., Bhaduri, B., Wang, S., Zhu, A.-X., Gahegan, M., Shekhar, S., Ye, X., McKenzie, G., Cervone, G., & Hodgson, M. E. (2025). GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS. Annals of GIS, 31, 501 - 536. https://doi.org/10.1080/19475683.2025.2552161

Liang, M., Su, J., Liu, R. W., & Lam, J. S. L. (2024). AISClean: AIS data-driven vessel trajectory reconstruction under uncertain conditions. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2024.117987

Liao, L., Zhao, Q., & Song, W. (2023). Monitoring of Oil Spill Risk in Coastal Areas Based on Polarimetric SAR Satellite Images and Deep Learning Theory. Sustainability. https://doi.org/10.3390/su151914504

Lieske, D., Avery‐Gomm, S., Champagne, P. S., & Fulton, L. (2025). GIS, Remote Sensing and Machine Learning: Data Integration to Support the Management of Coastal Island Ecosystems. Environmental Management, 75, 2625 - 2646. https://doi.org/10.1007/s00267-025-02202-5

Liu, R. W., Liang, M., Nie, J., Lim, W. Y. B., Zhang, Y., & Guizani, M. (2022). Deep Learning-Powered Vessel Trajectory Prediction for Improving Smart Traffic Services in Maritime Internet of Things. IEEE Transactions on Network Science and Engineering, 9, 3080-3094. https://doi.org/10.1109/tnse.2022.3140529

Liu, R. W., Nie, J., Garg, S., Xiong, Z., Zhang, Y., & Hossain, M. S. (2021). Data-Driven Trajectory Quality Improvement for Promoting Intelligent Vessel Traffic Services in 6G-Enabled Maritime IoT Systems. IEEE Internet of Things Journal, 8, 5374-5385. https://doi.org/10.1109/jiot.2020.3028743

Liu, R. W., Yuan, W., Chen, X., & Lu, Y. (2021). An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system. Ocean Engineering, 235, 109435. https://doi.org/10.1016/j.oceaneng.2021.109435

Lopac, N., Jurdana, I., Brnelić, A., & Krljan, T. (2022). Application of Laser Systems for Detection and Ranging in the Modern Road Transportation and Maritime Sector. Sensors (Basel, Switzerland), 22. https://doi.org/10.3390/s22165946

Lyu, M., Zhao, Y., Huang, C., & Huang, H. (2023). Unmanned Aerial Vehicles for Search and Rescue: A Survey. Remote. Sens., 15, 3266. https://doi.org/10.3390/rs15133266

Mahrad, B. E., Newton, A., Icely, J., Kacimi, I., Abalansa, S., & Snoussi, M. (2020). Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review. Remote. Sens., 12, 2313. https://doi.org/10.3390/rs12142313

Masria, A. (2024). Bridging Coastal Challenges: The Role of Remote Sensing and Future Research. Regional Studies in Marine Science. https://doi.org/10.1016/j.rsma.2024.103502

Melet, A., Teatini, P., Cozannet, G., Jamet, C., Conversi, A., Benveniste, J., & Almar, R. (2020). Earth Observations for Monitoring Marine Coastal Hazards and Their Drivers. Surveys in Geophysics, 41, 1489 - 1534. https://doi.org/10.1007/s10712-020-09594-5

Mishra, B., Garg, D., Narang, P., & Mishra, V. (2020). Drone-surveillance for search and rescue in natural disaster. Comput. Commun., 156, 1-10. https://doi.org/10.1016/j.comcom.2020.03.012

Morzaria-Luna, H., Turk-Boyer, P., Hernandez, J., Polanco-Mizquez, E., Downton-Hoffmann, C., Cruz-Piñón, G., Carrillo-Lammens, T., Loaiza-Villanueva, R., Valdivia-Jiménez, P. A., Sánchez-Cruz, A., Peña-Mendoza, V., López-Ortiz, A. M., Koch, V., Vázquez-Vera, L., Arreola-Lizárraga, J., Amador-Castro, I. G., Castillo, A. S. N., & Munguía-Vega, A. (2020). Fisheries management tools to support coastal and marine spatial planning: A case study from the Northern Gulf of California, Mexico. MethodsX, 7. https://doi.org/10.1016/j.mex.2020.101108

Murray, B., & Perera, L. (2021). Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness. Journal of Ocean Engineering and Science. https://doi.org/10.1016/j.joes.2021.03.001

Narayanan, K. J. S., & Manimaran, A. (2023). Recent developments in geographic information systems across different application domains: a review. Knowledge and Information Systems, 1-25. https://doi.org/10.1007/s10115-023-01969-5

Narayanan, K. J. S., & Manimaran, A. (2023). Recent developments in geographic information systems across different application domains: a review. Knowledge and Information Systems, 1–25. https://doi.org/10.1007/s10115-023-01969-5

Nascimento, V. D. D., Alves, T. A. O., Farias, C. M. D., & Dutra, D. (2024). A Hybrid Framework for Maritime Surveillance: Detecting Illegal Activities through Vessel Behaviors and Expert Rules Fusion. Sensors (Basel, Switzerland), 24. https://doi.org/10.3390/s24175623

Nasios, I., & Vogklis, K. (2025). AI at Sea, Year Six: Performance Evaluation, Failures,and Insights from the Operational Meta-Analysis of SatShipAI, a Sensor-Fused Maritime Surveillance Platform. Electronics. https://doi.org/10.3390/electronics14183648

Nayak, P. P., B, P. J., & Govindan, S. (2025). Leveraging geographic information system for dengue surveillance: a scoping review. Tropical Medicine and Health, 53. https://doi.org/10.1186/s41182-025-00783-9

Ngo, T. B., Ngo, L., Nguyen, D. T., Phi, A. V., Perera, A. G., & Nguyen, A. (2026). UAV-Based Visual Detection and Tracking of Drowning Victims in Maritime Rescue Operations. Drones. https://doi.org/10.3390/drones10020146

Nikouei, M., Baroutian, B., Nabavi, S., Taraghi, F., Aghaei, A., Sajedi, A., & Moghaddam, M. E. (2025). Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications. ArXiv, abs/2503.20516. https://doi.org/10.1016/j.iswa.2025.200561

Ning, H., Li, Z., Akinboyewa, T., & Lessani, M. (2024). An autonomous GIS agent framework for geospatial data retrieval. International Journal of Digital Earth, 18. https://doi.org/10.1080/17538947.2025.2458688

Nomikos, N., Gkonis, P., Bithas, P., & Trakadas, P. (2022). A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges. IEEE Open Journal of the Communications Society, 4, 56-78. https://doi.org/10.1109/ojcoms.2022.3225590

Nurfalah, A., Supangkat, S., & Mulyana, E. (2023). Effective & near real-time track-to-track association for large sensor data in Maritime Tactical Data System. ICT Express, 10, 312-319. https://doi.org/10.1016/j.icte.2023.07.010

Okafor-Yarwood, I. (2020). The Cyclical Nature of Maritime Security Threats: Illegal, Unreported, and Unregulated Fishing as a Threat to Human and National Security in the Gulf of Guinea. African Security, 13, 116 - 146. https://doi.org/10.1080/19392206.2020.1724432

Okafor-Yarwood, I. (2020). The Cyclical Nature of Maritime Security Threats: Illegal, Unreported, and Unregulated Fishing as a Threat to Human and National Security in the Gulf of Guinea. African Security, 13, 116–146. https://doi.org/10.1080/19392206.2020.1724432

Okafor-Yarwood, I., Eastwood, O., Chikowore, N., & De Oliveira Paes, L. (2024). Technology and maritime security in Africa: Opportunities and challenges in Gulf of Guinea. Marine Policy. https://doi.org/10.1016/j.marpol.2023.105976

Omar, O. E., Mahad, H., Gedi, O. A., Bashir, S. G., & Bilow, I. A. (2026). Revisiting the fisheries–piracy nexus in Somalia: illegal fishing, governance collapse, and maritime crime. Frontiers in Marine Science. https://doi.org/10.3389/fmars.2026.1821353

Ouellette, W., & Getinet, W. (2016). Remote sensing for Marine Spatial Planning and Integrated Coastal Areas Management: Achievements, challenges, opportunities and future prospects. Remote Sensing Applications: Society and Environment, 4, 138-157. https://doi.org/10.1016/j.rsase.2016.07.003

Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J. M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., . . . Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Journal of Clinical Epidemiology. https://doi.org/10.1016/j.jclinepi.2021.03.001

Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J. M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., . . . Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews.. Journal of clinical epidemiology. https://doi.org/10.1016/j.jclinepi.2021.03.001

Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J. M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., . . . Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Journal of Clinical Epidemiology. https://doi.org/10.1016/j.jclinepi.2021.03.001

Page, M., Moher, D., & McKenzie, J. (2021). Introduction to PRISMA 2020 and implications for research synthesis methodologists. Research Synthesis Methods, 13, 156 - 163. https://doi.org/10.1002/jrsm.1535

Page, M., Moher, D., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J. M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., . . . McKenzie, J. (2020). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. The BMJ, 372. https://doi.org/10.1136/bmj.n160

Paolo, F. S., Kroodsma, D., Raynor, J., Hochberg, T., Davis, P., Cleary, J., Marsaglia, L., Orofino, S., Thomas, C., & Halpin, P. N. (2024). Satellite mapping reveals extensive industrial activity at sea. Nature, 625, 85–91. https://doi.org/10.1038/s41586-023-06825-8

Park, H. Y., Suh, C., Woo, S., Kim, P., & Kim, K. (2022). Quality Reporting of Systematic Review and Meta-Analysis According to PRISMA 2020 Guidelines: Results from Recently Published Papers in the Korean Journal of Radiology. Korean Journal of Radiology, 23, 355 - 369. https://doi.org/10.3348/kjr.2021.0808

Park, H., Jung, J., Seo, M.-S., Choi, H., Cho, D., Park, S., & Choi, D.-G. (2025). AIS-LLM: A Unified Framework for Maritime Trajectory Prediction, Anomaly Detection, and Collision Risk Assessment with Explainable Forecasting. ArXiv, abs/2508.07668. https://doi.org/10.48550/arxiv.2508.07668

Park, S., & Song, A. (2023). Shoreline Change Analysis with Deep Learning Semantic Segmentation Using Remote Sensing and GIS Data. KSCE Journal of Civil Engineering, 28, 928 - 938. https://doi.org/10.1007/s12205-023-1604-9

Parums, D. (2021). Editorial: Review Articles, Systematic Reviews, Meta-Analysis, and the Updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, 27, e934475-1–e934475-3. https://doi.org/10.12659/msm.934475

Parums, D. (2021). Editorial: Review Articles, Systematic Reviews, Meta-Analysis, and the Updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines. Medical Science Monitor : International Medical Journal of Experimental and Clinical Research, 27, e934475-1 - e934475-3. https://doi.org/10.12659/msm.934475

Pastina, D., Santi, F., Pieralice, F., Antoniou, M., & Cherniakov, M. (2021). Passive Radar Imaging of Ship Targets With GNSS Signals of Opportunity. IEEE Transactions on Geoscience and Remote Sensing, 59, 2627-2642. https://doi.org/10.1109/tgrs.2020.3005306

Patel, K., Bhatt, C., & Mazzeo, P. (2022). Deep Learning-Based Automatic Detection of Ships: An Experimental Study Using Satellite Images. Journal of Imaging, 8. https://doi.org/10.3390/jimaging8070182

Peng, J., Wang, S., Mu, L., & Wang, S. (2024). Risk Assessment of Oil Spills along the Coastline of Jiaozhou Bay Using GIS Techniques and the MEDSLIK-II Model. Water. https://doi.org/10.3390/w16070996

Phayal, A., Gold, A., Maharani, C., Palomares, M. L., Pauly, D., Prins, B., & Riyadi, S. (2024). All maritime crimes are local: Understanding the causal link between illegal fishing and maritime piracy. Political Geography. https://doi.org/10.1016/j.polgeo.2024.103069

Pieri, G., Cocco, M., & Salvetti, O. (2018). A Marine Information System for Environmental Monitoring: ARGO-MIS. Journal of Marine Science and Engineering, 6, 15. https://doi.org/10.3390/jmse6010015

Qi, S., Lin, B., Deng, Y., Chen, X., & Fang, Y. (2024). Minimizing Maximum Latency of Task Offloading for Multi-UAV-Assisted Maritime Search and Rescue. IEEE Transactions on Vehicular Technology, 73, 13625-13638. https://doi.org/10.1109/tvt.2024.3384570

Qiao, D., Liu, G., Lv, T., Li, W., & Zhang, J. (2021). Marine Vision-Based Situational Awareness Using Discriminative Deep Learning: A Survey. Journal of Marine Science and Engineering, 9, 397. https://doi.org/10.3390/jmse9040397

Qingquan, L., Yi, L., Shuibo, H., Zhongwen, H., Hongzhong, L., Peng, L., Tiezhu, S., Chisheng, W., Junjie, W., & Guofeng, W. (2016). Review of remotely sensed geo-environmental monitoring of coastal zones. National Remote Sensing Bulletin. https://doi.org/10.11834/jrs.20166168

Qu, J., Liu, R. W., Guo, Y., Lu, Y., Su, J., & Li, P. (2023). Improving maritime traffic surveillance in inland waterways using the robust fusion of AIS and visual data. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2023.114198

Ramieri, E., Bocci, M., Brigolin, D., Campostrini, P., Carella, F., Fadini, A., Farella, G., Gissi, E., Madeddu, F., Menegon, S., Monaco, M. R., Musco, F., Soffietti, F., Barberi, L., & Barbanti, A. (2024). Designing and implementing a multi-scalar approach to Maritime Spatial Planning: The case study of Italy. Marine Policy. https://doi.org/10.1016/j.marpol.2023.105911

Ramovha, N., Mokoatle, M., Rathebe, P., & Sithole, T. (2026). Advancing Smart Water Loss and Oil Spillage Management: a Comprehensive Review of Remote Sensing and GIS Application. Water Resources Management. https://doi.org/10.1007/s11269-026-04508-3

Rangel, G. C., Da Silva Alves, V. B. A., De Araújo Costa, I. P., Moreira, M., De Araújo Costa, A. P., Santos, M., & Eckstrand, E. (2025). Efficient Naval Surveillance: Addressing Label Noise with Rockafellian Risk Minimization for Water Security. Water. https://doi.org/10.3390/w17030401

Rawson, A., & Brito, M. (2020). A critique of the use of domain analysis for spatial collision risk assessment. Ocean Engineering, 108259. https://doi.org/10.1016/j.oceaneng.2020.108259

Rawson, A., Brito, M., & Sabeur, Z. (2021). Spatial Modeling of Maritime Risk Using Machine Learning. Risk Analysis, 42. https://doi.org/10.1111/risa.13866

Rawson, A., Sabeur, Z., & Brito, M. (2021). Intelligent geospatial maritime risk analytics using the Discrete Global Grid System. Big Earth Data, 6, 294 - 322. https://doi.org/10.1080/20964471.2021.1965370

Rawson, A., Sabeur, Z., & Brito, M. (2021). Intelligent geospatial maritime risk analytics using the Discrete Global Grid System. Big Earth Data, 6, 294–322. https://doi.org/10.1080/20964471.2021.1965370

Razzaq, A. (2022). Blockchain-based secure data transmission for internet of underwater things. Cluster Computing, 25, 4495-4514. https://doi.org/10.1007/s10586-022-03701-4

Razzaq, A., Mohsan, S. A. H., Li, Y., & Alsharif, M. H. (2023). Architectural Framework for Underwater IoT: Forecasting System for Analyzing Oceanographic Data and Observing the Environment. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse11020368

Reggiannini, M., Salerno, E., Bacciu, C., D'Errico, A., Duca, A. L., Marchetti, A., Martinelli, M., Mercurio, C., Mistretta, A., Righi, M., Tampucci, M., & Di Paola, C. (2024). Remote Sensing for Maritime Traffic Understanding. Remote. Sens., 16, 557. https://doi.org/10.3390/rs16030557

Riveiro, M., Pallotta, G., & Vespe, M. (2018). Maritime anomaly detection: A review. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8. https://doi.org/10.1002/widm.1266

Sackey, A. D., Lomotey, B., Sackey, A. D., Lee, R. O.-D., Teye, A. A., Quarcoo, R., & Bansah, J. E. K. (2022). Delineating the relationship between maritime insecurity and COVID-19 pandemic on West African maritime trade. Journal of Shipping and Trade, 7. https://doi.org/10.1186/s41072-022-00121-w

Şahin, B. B., Erdaş, Ç., & Sümer, E. (2026). Multi-sensor data fusion in maritime surveillance: a review on methods and applications. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.3765

Saif, A. N. M., & Islam, M. A. (2022). Blockchain in human resource management: a systematic review and bibliometric analysis. Technology Analysis & Strategic Management, 36, 635 - 650. https://doi.org/10.1080/09537325.2022.2049226

Salam, A., Pranasari, T. E., Sasmita, W. S., & Paramashanti, B. (2026). Global trends and emerging themes in digital human resource management in healthcare: A bibliometric analysis.. Health services management research, 9514848261461230 . https://doi.org/10.1177/09514848261461230

Sanchez-Gonzalez, P.-L., Díaz-Gutiérrez, D., Leo, T., & Núñez-Rivas, L. R. (2019). Toward Digitalization of Maritime Transport?. Sensors (Basel, Switzerland), 19. https://doi.org/10.3390/s19040926

Sanchez-Gonzalez, P.-L., Díaz-Gutiérrez, D., Leo, T., & Núñez-Rivas, L. R. (2019). Toward Digitalization of Maritime Transport? Sensors, 19. https://doi.org/10.3390/s19040926

Santamaria, C., Alvarez, M., Greidanus, H., Syrris, V., Soille, P., & Argentieri, P. (2017). Mass Processing of Sentinel-1 Images for Maritime Surveillance. Remote. Sens., 9, 678. https://doi.org/10.3390/rs9070678

Santos, C. F., Agardy, T., Andrade, F., Crowder, L., Ehler, C., & Orbach, M. (2018). Major challenges in developing marine spatial planning. Marine Policy. https://doi.org/10.1016/j.marpol.2018.08.032

Sedaghat, A., Arbabkhah, H., Kang, M. J., & Hamidi, M. (2024). Deep Learning Applications in Vessel Dead Reckoning to Deal with Missing Automatic Identification System Data. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse12010152

Seyed, A. G., Ahmadi, A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M. M. I. S., Hamed, S., Moghaddam, A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., Brisco, B., S. M., & M. (2020). Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326-5350. https://doi.org/10.1109/jstars.2020.3021052

Sharma, S., Beslity, J. O., Rustad, L., Shelby, L. J., Manos, P. T., Khanal, P., Reinmann, A., & Khanal, C. (2024). Remote Sensing and GIS in Natural Resource Management: Comparing Tools and Emphasizing the Importance of In-Situ Data. Remote. Sens., 16, 4161. https://doi.org/10.3390/rs16224161

Snapir, B., Waine, T., & Biermann, L. (2019). Maritime Vessel Classification to Monitor Fisheries with SAR: Demonstration in the North Sea. Remote. Sens., 11, 353. https://doi.org/10.3390/rs11030353

Sohrabi, C., Franchi, T., Mathew, G., Kerwan, A., Nicola, M., Griffin, M., Agha, M., & Agha, R. (2021). PRISMA 2020 statement: What's new and the importance of reporting guidelines. International Journal of Surgery, 105918. https://doi.org/10.1016/j.ijsu.2021.105918

Sohrabi, C., Franchi, T., Mathew, G., Kerwan, A., Nicola, M., Griffin, M., Agha, M., & Agha, R. (2021). PRISMA 2020 statement: What's new and the importance of reporting guidelines.. International journal of surgery, 105918 . https://doi.org/10.1016/j.ijsu.2021.105918

Soldi, G., Gaglione, D., Forti, N., Simone, A. D., Daffinà, F., Bottini, G., Quattrociocchi, D., Millefiori, L. M., Braca, P., Carniel, S., Willett, P., Iodice, A., Riccio, D., & Farina, A. (2020). Space-Based Global Maritime Surveillance. Part I: Satellite Technologies. IEEE Aerospace and Electronic Systems Magazine, 36, 8-28. https://doi.org/10.1109/maes.2021.3070862

Song, Y.-S., Kalacska, M., Gašparović, M., Yao, J., & Najibi, N. (2023). Advances in geocomputation and geospatial artificial intelligence (GeoAI) for mapping. Int. J. Appl. Earth Obs. Geoinformation, 120, 103300. https://doi.org/10.1016/j.jag.2023.103300

Soulami, M., Benchekroun, S., & Galiulina, A. (2024). Exploring how AI adoption in the workplace affects employees: a bibliometric and systematic review. Frontiers in Artificial Intelligence, 7. https://doi.org/10.3389/frai.2024.1473872

Spinosa, A., Ziemba, A., Saponieri, A., Damiani, L., & Serafy, E. G. (2021). Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region. Journal of Marine Science and Engineering, 9, 575. https://doi.org/10.3390/jmse9060575

Syed, M. A. B., & Ahmed, I. I. (2023). A CNN-LSTM Architecture for Marine Vessel Track Association Using Automatic Identification System (AIS) Data. Sensors (Basel, Switzerland), 23. https://doi.org/10.3390/s23146400

Talbot-Jones, J., Macpherson, E., Jorgensen, E., Allison, A., Fisher, K., Hewitt, J., Paul, A., Rennie, H., & Zylla, A. (2025). Facilitating the ecosystem-based management transition in Aotearoa New Zealand. Journal of the Royal Society of New Zealand, 55, 1880 - 1896. https://doi.org/10.1080/03036758.2024.2426628

Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L. J., Adeli, S., & Brisco, B. (2020). Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. Isprs Journal of Photogrammetry and Remote Sensing, 164, 152-170. https://doi.org/10.1016/j.isprsjprs.2020.04.001

Thanopoulou, H., Patera, A., Moresis, O., Georgoulis, G., Lioumi, V., Kanavos, A., Papadimitriou, O., Zervakis, V., & Dagkinis, I. (2023). Supporting Informed Public Reactions to Shipping Incidents with Oil Spill Potential: An Innovative Electronic Platform. Sustainability. https://doi.org/10.3390/su152015035

Theodoropoulos, P., Spandonidis, C. C., Giannopoulos, F., & Fassois, S. (2021). A Deep Learning-Based Fault Detection Model for Optimization of Shipping Operations and Enhancement of Maritime Safety. Sensors (Basel, Switzerland), 21. https://doi.org/10.3390/s21165658

Thodi, M. F. C., Gopinath, G., Surendran, U., Prem, P., Al-Ansari, N., & Mattar, M. A. (2023). Using RS and GIS Techniques to Assess and Monitor Coastal Changes of Coastal Islands in the Marine Environment of a Humid Tropical Region. Water. https://doi.org/10.3390/w15213819

Thombre, S., Zhao, Z., Ramm-Schmidt, H., Garcia, J. V., Malkamaki, T., Nikolskiy, S., Hammarberg, T., Nuortie, H., Bhuiyan, M. Z. H., Särkkä, S., & Lehtola, V. (2020). Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review. IEEE Transactions on Intelligent Transportation Systems, 23, 64-83. https://doi.org/10.1109/tits.2020.3023957

Tu, E., Zhang, G., Rachmawati, L., Rajabally, E., & Huang, G. (2016). Exploiting AIS Data for Intelligent Maritime Navigation: A Comprehensive Survey From Data to Methodology. IEEE Transactions on Intelligent Transportation Systems, 19, 1559-1582. https://doi.org/10.1109/tits.2017.2724551

Valencia-Arias, A., Gómez-Bayona, L., Moreno-López, G., Sialer-Rivera, N., Bernal, O.-V., Gallegos, A., & Arias-Vargas, F. J. (2023). Research trends around open innovation in higher education: advancements and future direction. Frontiers in Education. https://doi.org/10.3389/feduc.2023.1146990

Vance, T., Wengren, M., Burger, E., Hernandez, D., Kearns, T., Medina-Lopez, E., Merati, N., O’brien, K., O’Neil, J., Potemra, J., Signell, R., & Wilcox, K. (2019). From the Oceans to the Cloud: Opportunities and Challenges for Data, Models, Computation and Workflows. Frontiers in Marine Science. https://doi.org/10.3389/fmars.2019.00211

Velástegui-Montoya, A., Montalvan-Burbano, N., Carrión-Mero, P., Rivera-Torres, H., Sadeck, L., & Adami, M. (2023). Google Earth Engine: A Global Analysis and Future Trends. Remote. Sens., 15, 3675. https://doi.org/10.3390/rs15143675

Vo, D., Nguyen, X., Nguyen, T., Hidayat, R., Huynh, T., & Nguyen, D. (2021). A review on the internet of thing (IoT) technologies in controlling ocean environment. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 47, 10064 - 10082. https://doi.org/10.1080/15567036.2021.1960932

Wang, C., Mouche, A., Tandeo, P., Stopa, J., Longépé, N., Erhard, G., Foster, R., Vandemark, D., & Chapron, B. (2019). A labelled ocean SAR imagery dataset of ten geophysical phenomena from Sentinel‐1 wave mode. Geoscience Data Journal, 6, 105 - 115. https://doi.org/10.1002/gdj3.73

Wang, H., Liu, Z., Liu, Z., Wang, X., & Wang, J. (2022). GIS-based analysis on the spatial patterns of global maritime accidents. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2022.110569

Wang, H., Liu, Z., Liu, Z., Wang, X., & Wang, J. (2022). GIS-based analysis on the spatial patterns of global maritime accidents. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2022.110569.

Wolsing, K., Roepert, L., Bauer, J., & Wehrle, K. (2022). Anomaly Detection in Maritime AIS Tracks: A Review of Recent Approaches. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse10010112

Won, W., Lim, M., & Kang, W. (2024). Estimating Accident Reduction Rate after Maritime Traffic Safety Assessment Using Synthetic Minority Oversampling Technique and Machine Learning Algorithm. Applied Sciences. https://doi.org/10.3390/app14083283

Wright, D., Janzen, C., Bochenek, R., Austin, J., & Page, E. (2019). Marine Observing Applications Using AIS: Automatic Identification System. Frontiers in Marine Science. https://doi.org/10.3389/fmars.2019.00537

Wu, J., Gan, W., Chao, H.-C., & Yu, P. S. (2024). Geospatial Big Data: Survey and Challenges. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 17007-17020. https://doi.org/10.1109/jstars.2024.3438376

Xia, H., Liu, Z., Maria, E., Liu, X., & Lin, C.-H. (2022). Study on City Digital Twin Technologies for Sustainable Smart City Design: a Review and Bibliometric Analysis of Geographic Information System and Building Information Modeling Integration. Sustainable Cities and Society. https://doi.org/10.1016/j.scs.2022.104009

Xin, X., Liu, K., Li, H., & Yang, Z. (2024). Maritime traffic partitioning: An adaptive semi-supervised spectral regularization approach for leveraging multi-graph evolutionary traffic interactions. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2024.104670

Xin, X., Liu, K., Loughney, S., Wang, J., Li, H., Ekere, N., & Yang, Z. (2023). Multi-scale collision risk estimation for maritime traffic in complex port waters. Reliab. Eng. Syst. Saf., 240, 109554. https://doi.org/10.1016/j.ress.2023.109554

Xu, G., Shi, Y., Sun, X., & Shen, W. (2019). Internet of Things in Marine Environment Monitoring: A Review. Sensors (Basel, Switzerland), 19. https://doi.org/10.3390/s19071711

Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023). A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools. IEEE Communications Surveys & Tutorials, 25, 2569-2598. https://doi.org/10.1109/comst.2023.3297395

Xu, S., Fu, Y., Xu, D., Han, S., Wu, M., Ju, X., Liu, M., Huang, D., & Guan, P. (2023). Mapping Research Trends of Medications for Multidrug-Resistant Pulmonary Tuberculosis Based on the Co-Occurrence of Specific Semantic Types in the MeSH Tree: A Bibliometric and Visualization-Based Analysis of PubMed Literature (1966–2020). Drug Design, Development and Therapy, 17, 2035 - 2049. https://doi.org/10.2147/dddt.s409604

Yang, C., Huang, Q., Li, Z., Liu, K., & Hu, F. (2017). Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth, 10, 13 - 53. https://doi.org/10.1080/17538947.2016.1239771

Yang, D., Wu, L., Wang, S., Jia, H., & Li, K. X. (2019). How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications. Transport Reviews, 39, 755 - 773. https://doi.org/10.1080/01441647.2019.1649315

Yang, J.-H., Yang, J.-Y., & Chang, Y. (2025). Toward Sustainable Development in the Ocean: A Framework for Blue Economy Marine Spatial Planning. Sustainable Development. https://doi.org/10.1002/sd.70183

Yang, T., Jiang, Z., Sun, R., Cheng, N., & Feng, H. (2020). Maritime Search and Rescue Based on Group Mobile Computing for Unmanned Aerial Vehicles and Unmanned Surface Vehicles. IEEE Transactions on Industrial Informatics, 16, 7700-7708. https://doi.org/10.1109/tii.2020.2974047

Yang, Y., Liu, Y., Li, G., Zhang, Z., & Liu, Y. (2024). Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review. Transportation Research Part E: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2024.103426

Yang, Y., Shao, Z., Hu, Y., Mei, Q., Pan, J., Song, R., & Wang, P. (2022). Geographical spatial analysis and risk prediction based on machine learning for maritime traffic accidents: A case study of Fujian sea area. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2022.113106

Yıldız, S., Uğurlu, Ö., Loughney, S., Wang, J., & Tonoğlu, F. (2022). Spatial and statistical analysis of operational conditions influencing accident formation in narrow waterways: A Case Study of Istanbul Strait and Dover Strait. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2022.112647

Yosep, I., Hikmat, R., Mardhiyah, A., & Kurniawan, K. (2026). Trends and research hotspots in digital interventions for recovery in Schizophrenia: A Bibliometric analysis (2016–2025). International Journal of Africa Nursing Sciences. https://doi.org/10.1016/j.ijans.2026.101026

Yu, H., Zhang, F., Yu, H., & Li, Y. (2025). A Multi-Criteria Framework for Sustainable Marine Spatial Planning in Coastal Cities: Case Study in Shenzhen, China. Sustainability. https://doi.org/10.3390/su17104480

ZekiAbdAlsammed, S. M. (2021). Advanced GIS-based Multi-Function Support System for Identifying the Best Route. Baghdad Science Journal. https://doi.org/10.21123/bsj.2022.19.3.0631

Zhan, H.-X., Zhang, Y., Huang, J., Song, Y., Xing, L., Wu, J., & Gao, Z. (2024). A reinforcement learning-based evolutionary algorithm for the unmanned aerial vehicles maritime search and rescue path planning problem considering multiple rescue centers. Memetic Computing, 16, 373 - 386. https://doi.org/10.1007/s12293-024-00420-8

Zhang, D., Zhan, J., Tan, L., Gao, Y., & Zupan, R. (2020). Comparison of two deep learning methods for ship target recognition with optical remotely sensed data. Neural Computing and Applications, 33, 4639 - 4649. https://doi.org/10.1007/s00521-020-05307-6

Zhang, Q., Fan, H., Qin, Y., & Zhou, Y. (2025). Advances in Interferometric Synthetic Aperture Radar Technology and Systems and Recent Advances in Chinese SAR Missions. Sensors (Basel, Switzerland), 25. https://doi.org/10.3390/s25154616

Zhang, T., Zhang, X., Liu, C., Shi, J., Wei, S., Ahmad, I., Zhan, X., Zhou, Y., Pan, D., Li, J., & Su, H. (2021). Balance learning for ship detection from synthetic aperture radar remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing. https://doi.org/10.1016/j.isprsjprs.2021.10.010

Zhang, W., Chen, G., & Yang, Z. (2025). Auction- and Pheromone-Based Multi-UAV Cooperative Search and Rescue in Maritime Environments. Drones. https://doi.org/10.3390/drones9110794

Zhang, X., Tan, R., Lam, W., Yao, L., Wang, X., Cheng, C.-W., Liu, F., Chan, J. C. P., Aixinjueluo, Q.-Y., Lau, C., Chen, Y., Yang, K., Wu, T., Lyu, A., & Bian, Z. (2020). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Chinese Herbal Medicines 2020 (PRISMA-CHM 2020).. The American journal of Chinese medicine, 1-35 . https://doi.org/10.1142/s0192415x20500639

Zhang, X., Zhang, C., Chen, X., & Su, P. (2024). Evaluation of the vulnerability of Huanghe estuary coastal wetlands to marine oil spill stress. Frontiers in Marine Science. https://doi.org/10.3389/fmars.2024.1481868

Zissis, D., Chatzikokolakis, K., Spiliopoulos, G., & Vodas, M. (2020). A Distributed Spatial Method for Modeling Maritime Routes. IEEE Access, 8, 47556-47568. https://doi.org/10.1109/access.2020.2979612

Perkembangan Pemanfaatan Geographic Information System (GIS) dalam Maritime Surveillance: Analisis Bibliometrik dan Systematic Literature Review

Abstract

Issue

Section

How to Cite

References

Most read articles by the same author(s)

Similar Articles

Article Sidebar

Main Article Content

Abstract

Article Details

Issue

Section

How to Cite

References

Most read articles by the same author(s)

Similar Articles