ForestIR Physics-Informed Forest Sound Simulation for Array-Based Bioacoustic Remote Sensing

Jul 16, 2026

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Microphone array-based passive acoustic monitoring is increasingly used for biodiversity sensing in forests, yet designing and evaluating array configurations remains difficult because real field recordings are costly, hard to reproduce, and offer limited control over forest structure and atmospheric conditions. ForestIR provides a physics-informed, reproducible simulation framework that generates source–microphone impulse responses under user-controlled conditions and renders synthetic array recordings via controlled convolution. Experiments demonstrate realistic localization sensitivity to forest layout and weather, with comparisons against field-measured sine-sweep impulse responses. ForestIR supports array design, robustness testing, and synthetic-data generation.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages22

Reading Time55 min

Abstract

Introduction

Motivation for Array Design and Localization

Limitations of Field Recordings and Existing Tools

Simulation Approaches and Their Trade-offs

arXiv :2607 .06299v1 [ ee ss .AS] 7 Jul 2026 ForestIR: Physics-Informed Forest Sound Simulation for Array-Based Bioacoustic Remote Sensing Xin Shen 1 , Jennifer N. Kampe 1,2 , Changwoo J. Lee 1 , Braden Scherting 1 , Panu Somervuo3 , Ari Lehti¨o4 , Sandro von Brandenburg4 , Ossi Nokelainen2,5 , Otso Ovaskainen2 , and David B. Dunson 1 1 Department of Statistical Science, Duke University, Durham, NC, USA 2 Department of Biological and Environmental Science, University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland 3 Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland 4 Digital Services, University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland 5 Open Science Centre, University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland Abstract Microphone array-based passive acoustic monitoring is increasingly used for biodiversity sensing in forests. However, design and evaluation of array systems and configurations remains difficult since field recordings are costly, difficult to reproduce, and provide limited control over forest and atmospheric conditions. We present ForestIR, a physicsinformed and reproducible simulation framework that links forest and environmental conditions to microphone-array recordings for bioacoustic remote sensing. Through a more realistic sound propagation method and a systematic control over array design and environmental factors, ForestIR provides a practical simulation framework for optimizing array-based monitoring systems, especially for sound source localization purposes. ForestIR generates source–microphone impulse responses (IRs) under user-controlled forest and atmospheric conditions, and renders synthetic array recordings by convolving test signals with controlled background noise. We evaluate and demonstrate realistic features of ForestIR through experiments based on localization sensitivity to forest layout and atmospheric conditions, and also comparison between simulated IRs with sine-sweep IR measurements from a field experiment. ForestIR provides a practical way to test how forest and ground conditions, atmospheric state, and array geometry affect bioacoustic localization, and can support microphone-array design, robustness testing, and synthetic-data generation for passive acoustic monitoring. Keywords: bioacoustic remote sensing; impulse response; forest acoustics; sound propagation; sound source localization [Correspondence: xin.shen@duke.edu](Correspondence: xin.shen@duke.edu) (Xin Shen). [Senior authors: otso.t.ovaskainen@jyu.fi](Senior authors: otso.t.ovaskainen@jyu.fi) (Otso Ovaskainen), [dunson@duke.edu](dunson@duke.edu) (David B. Dunson). 1 Introduction Passive acoustic monitoring (PAM) has become increasingly important in biodiversity monitoring due to difficulties in detecting wildlife by sight in forests. Compared to traditional surveys, which comes with much higher labor and time cost, PAM can produce data over substantially larger areas and longer periods [Pettorelli et al. , 2016 , Allan et al. , 2018 , Berger-Tal and LahozMonfort, 2018 , Stephenson, 2020 , Lahoz-Monfort and Magrath, 2021] . For vocal species such as birds, bats and cicadas, acoustic sensing works especially well, and is now a common tool for biodiversity assessment and conservation [Gibb et al. , 2019 , Sugai et al. , 2019 , Stowell and Sueur, 2020] . We are particularly motivated by the problem of designing array systems for sound source localization purposes. Simple PAM systems are effective for monitoring the presence or absence of vocal species, but collecting acoustic data with detailed information on sound source locations is a challenging task. Such location information is important because it provides deeper insight into which species are present and where they occur in a detailed manner. By synchronizing the microphone arrays, it is possible to estimate where the calls are originating from based on the time diff

FAQs

What problem does ForestIR address in passive acoustic monitoring?

ForestIR targets the challenge of designing and evaluating microphone array systems for sound source localization when field recordings are expensive, difficult to reproduce, and limited in controlling forest and atmospheric conditions.

How does ForestIR generate synthetic microphone array recordings?

ForestIR creates source–microphone impulse responses (IRs) using physics-informed sound propagation under user-controlled forest and atmospheric settings, then renders synthetic recordings by convolving test signals with controlled background noise.

How is ForestIR validated in the provided content?

The framework’s realism is demonstrated through experiments testing localization sensitivity to forest layout and atmospheric conditions, and through comparisons between simulated IRs and sine-sweep IR measurements from a field experiment.

Jul 16, 2026

Upload by Ezra