Case Study: How can dMRV Support High Quality Carbon Credits?

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What is MRV?

Traditional MRV stands for a process used to Measure, Report, and Verify the impact of carbon mitigation initiatives. It involves collecting data on the project's initial emissions, measuring the actual emissions, and then comparing both to determine the carbon reduction achieved.

It is characterised by:

  1. Monitoring: Consistently observing and measuring project activities, including tracking emission levels, resource usage, or the performance of emission reduction measures. This process employs various tools and methodologies such as sensors, data collection systems, and on-site observations.
  2. Reporting: The systematic documentation and presentation of the monitored information, which can vary in format from detailed technical reports to concise summaries for public disclosure. This facet is often mandated by regulatory bodies and serves as a means for transparency and stakeholder communication.
  3. Verification: The independent assessment process aimed at confirming the accuracy of reported data. This involves expert review and analysis to ensure data integrity and compliance with standards or regulations. Verification is crucial for validating the efficacy of emissions reduction endeavours and upholding credibility.

What is dMRV?

Digital MRV, or dMRV, refers to all those practices that enhance the traditional MRV process through the use of digital technologies, such as remote sensing, data analytics, and blockchain solutions that streamline and improve environmental data management.

It is a critical tool to create higher standards of integrity, and bring increased transparency, scale, and accountability to the voluntary carbon market.

dMRV is a newer approach to monitoring and evaluating climate change mitigation efforts that utilises digital technologies and data analytics.

Specifically, dMRV has proven to significantly improve the Monitoring, Reporting and Verification process of projects within the Voluntary Carbon Market (VCM), by increasing a set of new measures such as:

  • Integration of Digital Tools and Data Collection: Digital MRV facilitates precise, real-time data collection by integrating digital tools, thus streamlining the MRV process for enhanced efficiency and reliability. It uses technologies like sensors, satellites, and remote sensing for more accurate, timely, and comprehensive data collection on a larger scale. This also provides more transparent and accessible reporting mechanisms, enabling projects to grow at scale.
  • Automation: Digital MRV automates many of the data collection and analysis processes, reducing the need for human intervention, the risk of potential quantification errors and improving efficiency. This can result in faster reporting and decision-making.
  • Transparency: Digital MRV provides greater transparency and accountability by making data available in real-time and in a more accessible format. This can improve trust between stakeholders and increase the likelihood of achieving climate change goals.
  • Cost-effectiveness: Digital MRV can be more cost-effective than traditional MRV, as it reduces the need for manual data collection and analysis. It also allows for more targeted interventions, which can improve the cost-effectiveness of mitigation efforts.
  • Scope: Digital MRV can capture a wider range of data than traditional MRV, including indirect and long-term effects, which can provide a more comprehensive understanding of the impact of mitigation efforts.

The gradual evolution and adoption of cutting-edge technology have paved the way for Digital MRV (dMRV) solutions to bolster the Voluntary Carbon Market (VCM) across various critical fronts:

Examples of dMRV

  • Satellite Imagery: Orbiting satellites capture images of the Earth's surface, offering crucial insights into changes in land cover, such as deforestation and afforestation. This imagery plays a vital role in estimating the potential for carbon sequestration and verifying carbon offset projects related to forestry and land-use changes.
  • Blockchain: By integrating Blockchain technology with dMRV, dynamic carbon credit tokens can be created, providing real-time updates to reflect the ecological asset's true value. This integration also enables the creation of "vintages" that represent the current status of the asset. The combination of blockchain and dMRV enhances transparency and accountability by establishing a tamper-proof record of transactions, preventing fraud, and facilitating secure, efficient transfers without intermediaries. Criticisms surrounding carbon financing and conservation projects underscore the necessity of a robust MRV system to ensure the effectiveness of carbon mitigation projects.
  • LiDAR: LiDAR, a remote sensing technology utilising laser pulses, is utilised in carbon credit projects to assess forest canopy height and structure. This technology provides crucial data for estimating carbon sequestration potential, particularly in reforestation and afforestation efforts.
  • Acoustic monitoring: Acoustic monitoring involves using digital microphones to record and analyse vocalisations and other sounds (including ultrasound) emitted by living organisms, such as wildlife. In carbon credit applications, this technology aids in assessing ecosystem health and biodiversity, offering valuable insights into the impact of conservation and reforestation efforts on wildlife and ecosystem quality.

Case Study: dMRV to measure Biodiversity with

Why measure and monitor biodiversity?

Many projects within the Voluntary Carbon Market (VCM) support ecosystem conservation and restoration. To assess the impact of these projects, the presence and richness of biodiversity represents a fundamental outcome metric. However, current tools to measure, report and verify biodiversity status are extremely labour intensive and habitat invasive. Additionally it is highly complex to quantify biodiversity conservation and restoration efforts. For this reason many projects don't report biodiversity impacts accurately, opting for oversimplified assessments. This hampers the market's ability to reward projects with greater biodiversity benefits and discourages developers from improving metrics. Adopting quantitative approaches to biodiversity assessment enables projects to be rewarded for actual biodiversity benefits, fostering a cycle that enhances biodiversity and carbon sequestration as well as building trust and pushing forward radical transparency within the VCM space.

In order to face the challenge, has developed a holistic, data-informed, and AI-powered  dMRV approach that includes acoustic monitoring to accurately assess a habitat’s biodiversity.

How does it work?

A significant number of species from almost all taxonomic groups (e.g.,amphibians, birds, mammals, and insects) vocalise or employ sound for communication, opening up acoustic monitoring as an effective tool for biodiversity assessment and monitoring at scale.

By placing small microphones within a natural habitat, Passive Acoustic Monitoring (PAM) facilitates uninterrupted, non-intrusive surveys to ascertain the presence and abundance of different species based on their acoustic signals. The collection of calls and sounds coming from living organisms is referred to as bioacoustics.

Additionally it also facilitates the analysis of soundscapes that are the collection of all sounds in a certain space and time. Soundscape sampling – or ecoacoustics – can be used to assess ecological communities and how they change over time.

PAM can be particularly efficient at detecting elusive species that are challenging to study through conventional ecological surveys. As well as the potential presence of human activity within the restoration/conservation area.

Passive Acoustic Monitoring (PAM) facilitates the collection of invaluable data for estimating population sizes, tracking anthropogenic pressures like illegal logging, safeguarding projects from potential greenwashing claims, and providing readily accessible data to meet third-party audit requirements.

An example of the dMRV technology that biometrio uses in their projects
A small microphone is placed within the habitat to collect acoustic information

Analysis of acoustic recordings

Once the acoustic information has been collected, experts within combine deep learning techniques with soundscape analysis to provide an in-depth assessment of sound-producing animals and human disturbances.

Experts create artificial intelligence models to identifying different animals in the acoustic recordings collected from the field. These models require extensive training datasets (e.g., annotated acoustic datasets), in order to identify entire vocalising communities down to the species level, and are currently mostly available for birds, frogs, and bats. Developing or securing comprehensive annotated acoustic datasets remains a challenge, especially for the tropics, where ecosystems are highly diverse and reference acoustic libraries are still missing for most species.

But the more projects or areas produce acoustic recordings, the better and more comprehensive the datasets will become.

Furthermore, creating acoustic archives of different landscapes at different points of time will contribute immensely to understanding biodiversity changes and challenges, as we will always be able to analyse recordings retrospectively (with the constantly improving datasets).

Expert human input will, however, remain essential for understanding and interpreting biodiversity information, and for making value judgements about it. Additionally, citizen scientists and local communities also play a big role in helping identify species and collecting acoustic recordings, therefore opening up possibilities for carbon projects to be more inclusive as well.

How the dMRV recordings are interpreted to detect biodiversity

Integrating diverse biodiversity data has pioneered a comprehensive approach to acoustic monitoring, uniting cutting-edge techniques in ecoacoustics and bioacoustics through advanced deep learning models. By harnessing acoustic indices, their technology deciphers intricate layers of the soundscape, revealing the diverse communities of animals within. Through species recognition models, they accurately identify individual species from acoustic recordings, validating patterns observed at the soundscape level. This synergistic fusion of methodologies and technology empowers them to offer thorough and holistic assessments of biodiversity, exploring the composition, richness, and ecological interactions within ecosystems.‘s dMRV solutions seamlessly integrate wildlife cameras and remote sensing monitoring, augmenting the understanding of biodiversity and ecosystem conditions. Collaborating with clients, they unveil the mysteries both above and below the forest canopy, providing insight not only through visual observation but also through the power of sound.

Transforming the voluntary carbon market with dMRV

Digital MRV approaches are fundamental for enhancing the transparency, financing, and scalability within the nature-based solutions space. By harnessing digital technologies, these approaches transform traditional MRV processes as they can produce precise data insights at scale with high efficiency and low costs.

This heightened transparency not only mitigates the risk of fraudulent activities but also instills market credibility, crucial for attracting financing. Moreover, dMRV can streamline operations, minimising manual efforts and bureaucratic hurdles, thereby facilitating the scalability of nature-based solutions projects.

Acoustic monitoring has emerged as a potent tool for biodiversity assessment and monitoring at scale. Measuring biodiversity in carbon projects is essential due to biodiversity’s fundamental role in ecosystem resilience and functioning (including carbon sequestration), clean water, and habitat provision. Rigorous measurement is necessary for combating biodiversity loss and ensuring the effectiveness of nature-based climate solutions. Through the quantification of biodiversity impacts, carbon buyers can incentivise developers to prioritise interventions with enhanced biodiversity benefits, fostering a virtuous cycle that enhances biodiversity alongside carbon sequestration. Additionally, measuring biodiversity provides vital data for adaptive ecosystem management, addressing anthropogenic pressures, and engaging local stakeholders, thus promoting connectivity to nature and fuelling nature-based economies.

Passive acoustic monitoring (PAM) can produce valuable biodiversity data on species presence, population sizes, and habitat quality, thereby providing insights into ecological communities and their changes over time. At, the integration of advanced ecoacoustic analysis with deep learning-based bioacoustics enables comprehensive assessments of biodiversity. By using acoustic indices and species recognition models, experts decode soundscape layers and identify specific animal species with precision and efficiency, delving into the composition, richness, and ecological interactions within ecosystems. Through this holistic approach that can also integrate wildlife cameras and remote sensing, can provide a thorough understanding of biodiversity and ecosystem conditions, offering valuable insights for informed ecosystem management decisions.


Digital MRV (dMRV) presents a paradigm shift in monitoring, reporting, and verifying climate change mitigation efforts, leveraging digital technologies to enhance the traditional MRV process. By integrating tools such as remote sensing, data analytics, and blockchain solutions, dMRV not only improves the accuracy and efficiency of environmental data management but also fosters higher standards of integrity, transparency, and accountability within the voluntary carbon market (VCM).

dMRV's capacity to integrate diverse data sources and automate processes not only reduces costs and human errors but also expands the scope of monitoring to include indirect and long-term effects. This comprehensive approach enables stakeholders to make informed decisions and fosters trust between participants, ultimately advancing climate change goals.

The innovative application of dMRV in biodiversity monitoring, exemplified by, demonstrates its transformative potential. Through advanced techniques in ecoacoustics and bioacoustics, coupled with deep learning models and remote sensing data, dMRV enables the accurate assessment of biodiversity, offering holistic insights into ecological interactions within ecosystems. By seamlessly integrating diverse biodiversity data sources, including acoustic recordings, wildlife cameras, and remote sensing monitoring, dMRV solutions elevate our understanding of ecosystem conditions, paving the way for more effective conservation and restoration efforts.

As digital technologies continue to evolve, dMRV stands as a critical tool in advancing environmental sustainability, facilitating real-time monitoring, and ensuring the effectiveness of climate change mitigation strategies in the years to come. Finding its core values on data transparency, Senken backs projects capable of delivering detailed information, partnering exclusively with initiatives that embrace cutting-edge dMRV solutions, exemplified by pioneers like

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