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Since their inception in the 1970s, multibeam echo sounders (MBES) have transformed seafloor mapping, delivering high-resolution bathymetric data with unprecedented detail. Today, MBES technology goes beyond depth measurement by exploiting seafloor and water column backscatter to characterize seafloor properties and to detect, visualize and quantify acoustic targets such as gas bubbles, suspended matter and biological or anthropogenic structures within the water column. Over the past two decades, MBES backscatter has become a cornerstone of marine research, driving advancements in habitat mapping, marine geology, and environmental monitoring, with increasing applications in autonomous surveys and machine-learning-driven seafloor classification. However, unlike bathymetric measurements of the seafloor, where established standards exist which are primarily governed through the International Hydrographic Organization (IHO), no such standards exist for the collection, processing and use of MBES backscatter measurements. To obtain reliable and comparable measurements that reflect true seabed variations (rather than instrument variations) it is necessary to understand how seafloor backscatter data are recorded by sonar systems from different manufacturers, and how the measurements are influenced by various procedures for data acquisition and processing, as well as environmental factors. MBES backscatter data acquisition and analysis has unequivocally matured into a specialist discipline in its own right, demanding advanced expertise in acoustics, system calibration, signal processing, and environmental interpretation. Without such dedicated competencies, the full scientific and operational value of MBES backscatter data cannot be reliably realized, nor can results be meaningfully compared across systems, surveys, or studies. To address some of these challenges, the GeoHab association (www.geohab.org) established the Backscatter Working Group (BSWG) in 2013, leading to the publication in 2015 of the report, "Backscatter measurements by seafloor-mapping sonars. Guidelines and Recommendations" (Lurton et al., 2015), which provided a foundational reference for MBES backscatter data. However, as the field has continued to evolve over the subsequent decade, a reassessment of methodologies, technologies, and research priorities has become imperative. This Research Topic in Frontiers in Remote Sensing, entitled Multibeam Echosounder Backscatter: Advances and Applications, meets this need by presenting the most contemporary and innovative research covering methodological advances, evolving community priorities, and new applications of MBES backscatter data. This collection of articles represents the evolving broad spectrum of applications and methods, showcasing fresh techniques for analyzing MBES backscatter data and demonstrating its role as a unifying resource in marine science (Figure 1). A crucial aspect of this new collection of research articles is the similarity of user expectations between 2015 and 2025. The 2015 BSWG report shared the concerns of the MBES backscatter users community regarding consistency, calibration, and processing methodologies (Lurton et al., 2015) and these concerns hold true 10 years on, with the necessity for absolute calibration, standardized quality control, and interoperability with other datasets identified as priorities of the community (Lecours et al., 2025).The articles within this collection are summarized in Table 1, including their primary research focuses and methodological emphases. The broad methodological themes include improvements in calibration methods to ensure consistency across different sonar systems (Le Bouffant et al., 2025;Roche et al., 2025), refined data acquisition strategies incorporating multi-frequency MBES backscatter (Menandro et al., 2024;Schulze et al., 2025), and new modelling approaches and innovative processing techniques that enhance the accuracy and usability of seafloor Backscatter Strength (BS) derived information (Fezzani et al., 2025;Fonseca et al., 2025). Another significant theme is the increasing development of open-source software for MBES backscatter data processing (Poncelet et al., 2025a(Poncelet et al., , 2025b)).Advances in open-source processing algorithms and analytical tools have democratized the use of MBES backscatter data, facilitated standardized methodologies and improved data accessibility across the scientific community. This software development is expected to accelerate the adoption of best practices and enhance collaboration among researchers worldwide. Additionally, the benefits of integrating machine learning approaches for automated interpretation and modelling of MBES backscatter datasets have been demonstrated in several studies (Berry et al., 2025;Berry and Nanlal, 2025;Menandro et al., 2024;Perret et al., 2025), unlocking new potential for seabed-habitat classification, enhanced analysis and decision-making.Significant progress has been made in establishing a collaborative exchange between the communities of users of backscatter data from Single Beam Echosounders (SBES) and MBES to resolve issues related to calibration (Le Bouffant et al., 2025;Roche et al., 2025). The discovery of a significant influence of temperature on the physical characteristics of MBES arrays and, as a result on the BS, uncovered a necessity to systematically consider water temperature during MBES backscatter data acquisition and processing (Roche et al., 2025). Another highlight of this collection is the widespread use of multi-frequency MBES backscatter (often referred to as "multispectral backscatter") with several articles on this theme (Table 1). This popularity is due to multispectral backscatter opening new possibilities for seafloor characterization through its more precise differentiation of substrate types (Menandro et al., 2025). The processing, visualization and quantification of water column backscatter data have also emerged over the past decade, with significant innovation leading to a wide range of uses, such as gas seepage detection (Perret et al., 2025), habitat characterization (Berry and Nanlal, 2025), and long line aquaculture (Vandorpe et al., 2026).The case studies presented in this Research Topic illustrate the multifaceted applications of MBES backscatter data, encompassing studies of sediment transport, habitat mapping, deep-sea exploration, and marine resource management (Table 1). The integration of MBES backscatter data with other geospatial and oceanographic datasets has proven particularly valuable in interdisciplinary research, enhancing our ability to characterize marine environments. This collection of articles demonstrates that while the concerns of MBES backscatter data users have not significantly changed in the decade since the BSWG 2015 report, the technologies and methodologies involved certainly did. Thus, we foresee that the future of MBES backscatter data research will continue to be shaped by technological advancements. We may expect new technological developments on the part of system manufacturers, following seafloor and water-column multispectral backscatter data, new software developments on the part of the open-source community, and new methodological developments on the part of the research community, in particular using artificial intelligence (AI), which is the technological revolution of our current decade (and more?). These developments will need to be counterbalanced by the establishments of standards, in particular in terms of calibration and data quality. As the scientific community continues to develop technology and address challenges, collaboration among researchers, hydrographers, industry stakeholders, and policymakers will be essential to ensure that MBES backscatter remains a powerful tool for marine cartography, habitat mapping, environmental monitoring, and sustainable resource management. The articles in this Research Topic individually contribute to this ongoing effort, while the collection itself provides a snapshot in time of the current concerns, interests and advancements of the MBES backscatter users community.