Handbook on "Passive Acoustic Monitoring in Surface and Underwater Environments: Recent Advances with Machine Learning and Signal Processing Concepts"

T. Bouwmans,  A. Zakharova, C. Isaza, M. Bolgan 

• Publisher: CRC Press, Taylor and Francis Group. [Purchase]

  • Tentative publication date:  June 30, 2026

• Preface introducing the field of Passive Acoustic Monitoring in Surface and Underwater Environments, and the different chapters:

This handbook solicited contributions in the field of  Passive Acoustic Monitoring. By incorporating both existing and new ideas, this handbook gives a complete overview of the concepts, theories, algorithms, and applications related to  Passive Acoustic Monitoring using recent advances on machine learning and signal processing. Moreover, an accompanying website is provided. This website contains the list of chapters, their abstract and links to the demos. It allows the reader to have a quick access to the main resources, datasets and codes in the field. Finally, with this handbook, we aim to bring a one-stop solution, i.e., access to a number of different solutions for PAM in surface and underwater environments. The handbook consists of tow parts.

This website contains the list of chapters, their abstract and links to the demos. It allows the reader to have a quick access to the main resources, datasets and codes in the field.

• About the editors: T. Bouwmans, A. Zakharova, C. Isaza, M. Bolgan  (more details)

• List of contributors:  The contributors are representative researchers in the field. (more details)

• Contents (2 Parts, 10 Chapters)

Part I. Surface Acoustic Monitoring

Chapter 1 - Individual Animal Identification through Bioacoustics

Jonathan Gallego Londoño (Universidad de Antioquia UdeA,Colombia), Juan David Martínez-Vargas (Universidad EAFIT, Colombia), José David López (Universidad de Antioquia UdeA,Colombia)

Chapter 2 - Monitoring the Spatial Movement of Multiple Individuals using Sound

Carol L. Bedoya (DigiLab, New Zealand), Laura E. Molles (DigiLab, New Zealand)

Chapter 3 - From Brain Connectomes to Soundscape Connectomes: Representing Acoustic Landscape Heterogeneity Using Graph-Based Networks

Cesar Uribe (Rice University, U.S.A), María José Guerrero Muriel (Universidad de Antioquia UdeA, Colombia), Claudia Victoria Isaza Narváez (Universidad de Antioquia UdeA, Colombia)

Chapter 4 - Mitigating Domain Shift in Bioacoustics: Adapting Foundation Models for Passive Acoustic Monitoring

Jhony H. Giraldo (LTCI, Telecom Paris, France), Julian D. Santamaria (Universidad de Antioquia UdeA, Colombia) , Claudia Isaza (Universidad de Antioquia UdeA, Colombia)

Chapter 5 - Automatic Source Separation in Avian Duets and Countersongs using Deep Neural Network

Laura E. Molles (DigiLab, New Zealand), Daniela Cuartas-Marulanda (Universidad de Antioquia UdeA, Colombia), Carol L. Bedoya (DigiLab, New Zealand)

 Part II. Underwater Acoustic Monitoring

Chapter 1 - Unsupervised Domain Adaptation via Data Pruning for Enhancing the Robustness of PAM Systems        

Andrea Napoli, Paul White (Institute of Sound and Vibration Research. University of Southampton, UK)

Chapter 2 - Machine Learning Meets Ecoacoustics: Challenges and Opportunities in Analyzing Complex Signals from Marine Mammals       

Fernando Luis Rosa González (Grupo de Bioacústica Física y Multisensores Distribuidos, Universidad de La Laguna. Spain)

Chapter 3 - The Influence of Input Representation and Major Soundscape Drivers on Acoustic Indices in the West Coast of Scotland   

Benedict Dell (Institute of Sound and Vibration Research. University of Southampton, UK)

Chapter 4 - From Sounds to Biodiversity Management: Fish Bioacoustics for Conservation           

Marta Bolgan (Fugro, UK)

Chapter 5 - Underwater Sounds Classification for Effective Smart Marine Monitoring Systems       

Fabio Narducci (CVPR Lab, University Parthenope of Naples, Italy)