Rapid Recap: NTx Ground Truth with Dr Max Bodmer of RePlanet

Authored by Daniel Swid

Event Summary

This morning, together with Sylvain Vaquer , Gunthar Hartwig , and featuring Dr. Max Bodner of rePLANET , we hosted an interactive participatory workshop leveraging visual communication to accelerate shared understanding with over 60 RSVPs and just over 40 attendees.

Event Details

Session 1 –?Drivers of Nature Data with rePlanet, 11 April

What are the drivers of nature data? Some drivers include biodiversity credits, supply chain analysis, portfolio risk mitigation, regulatory compliance such as CSRD, payment for ecosystem services and more. In this event we heard from Dr Max Bodmer of rePlanet including examples from Sylvain of Mozaic Earth. Participants then explored patterns together to help advance shared understanding towards structuring products and services to account for various drivers and challenges of nature data collection.

Rapid Recap

Below is a quick play by play of how the group worked together during our time together.

What does ground truth mean to you?

Summary generated via Nature Data Nexus GPT

1. Essential Baseline for Models: In situ sensing is seen as a critical baseline against which models are trained, emphasizing the importance of direct, on-the-ground measurements for calibrating and validating models, especially those based on remote sensing data.
2. Reliability and Minimal Processing: The value of reliable, minimally processed data is highlighted, suggesting a preference for data that is close to its original form and thus more directly reflective of reality.
3. Calibration and Validation (Cal/Val): Calibration and validation of spaceborne and remote sensing data are crucial. This points to the ongoing need to align remote measurements with actual on-the-ground conditions to ensure accuracy and reliability.
4. Field Data Verification: There's a strong emphasis on field data for the verification or validation of remote or satellite data, underlining the indispensable role of direct observations in ensuring the trustworthiness of data derived from technology.
5. Accuracy, Precision, and Suitability: Ground truth is associated with the need for data to be accurate (close to the true value), precise (reproducible), and suitably representative of reality, ensuring that data truly reflects the phenomena it purports to measure.
6. Complement to Satellite Data: Ground truth is seen as a required partner to satellite data, essential for the interpretation and validation of observations made from afar.
7. Evidentiary Basis: The concept of building evidence packages over time series to substantiate claims suggests a longitudinal approach to collecting and analyzing ground truth data to support or refute hypotheses over time.
8. Credibility and Baseline Establishment: Ground truth provides a credible baseline against which changes and phenomena can be measured, serving as a point of reference for assessing transformations or stasis in the environment.
9. Capturing Nuance: The ability to capture the nuances of environmental conditions that remote sensing might overlook, emphasizing the depth and detail that direct observations can provide.
10. Verification of Claims: Ground truth serves as a means to verify claims made based on remote sensing or theoretical models, ensuring that assertions about environmental conditions are rooted in actual observations.
11. Engagement with Local and Indigenous Communities: This highlights the importance of incorporating traditional knowledge and local observations into scientific research, recognizing the value of diverse perspectives in understanding and interpreting ground truth data.
12. Methodological Rigor: The mention of sampling, field readings, protocols, lab analysis, and statistical significance underscores the methodological rigor required in collecting and analyzing ground truth data to ensure its reliability and validity.

Overall, ground truth is viewed as a foundational element in environmental science and policy, crucial for validating remote sensing data, ensuring the accuracy and reliability of models, and providing a direct connection to the physical world that these models seek to represent.

Who needs ground truth data?

Summary generated via Nature Data Nexus GPT

1. Universal Necessity: A broad acknowledgment that virtually "Everyone" benefits from ground truth data, suggesting its fundamental role across disciplines, sectors, and activities related to land, environment, and beyond.
2. Environmental and Land Management: This includes "Land stewards," "Forest Stewards," and those involved in managing and conserving natural resources. Ground truth data supports sustainable practices, conservation efforts, and environmental stewardship.
3. Project Development and Management: Repeated mentions of "Project developers," "Project managers," and "Project Validators" indicate the critical role of ground truth data in planning, implementing, and validating projects, especially those with environmental impacts or dependencies.
4. Earth Observation and Remote Sensing: Entities like "Earth Observation" groups, "Remote sensing companies," and "Satellite missions" require accurate ground truth data for calibration, validation, and enhancing the interpretability of satellite and aerial data.
5. Financial and Corporate Sectors: The "Financial Services Industry," "Corporates with nature-based goals/targets," and "Financers" show the growing recognition of ground truth data in risk management, investment decision-making, and achieving sustainability targets. This includes adherence to regulations and standards like the "CSRD" (Corporate Sustainability Reporting Directive) in Europe.
6. Food and Drinks Sector: This sector's inclusion highlights the importance of ground truth data in sustainable agriculture, supply chain management, and ensuring the environmental integrity of products.
7. Advisory and Accreditation: "Advisors" and "Project accreditors" rely on ground truth data to provide informed guidance, ensure compliance with standards, and accredit projects based on their environmental impact and sustainability.

Overall, the responses underscore the cross-sectoral demand for ground truth data, highlighting its integral role in environmental management, project development, compliance, and sustainability efforts across the globe.

Case Studies from RePlanet

The group heard an overview of rePlanet from Max followed by a number of case studies across different part of the world.

Breakout Groups; Groundtruth Data Drivers; Nature Data Consumers, Requirements, and Constraints

Participants then worked together in small breakouts on their own use cases, both real projects and hypothetical. The small groups then presented back and this helped to accelerate shared understanding among participants including the challenge and constraints of ground truth nature data.

Thank you for reading this rapid recap —?don't miss the next session!

Session 2

Summary – Earth Observation with Kanop, 30 April

Where does earth observation meet in situ data collection? When it comes to nature data, there are various indicators and variables that can be observed remotely and these have their limits. In this event we'll hear from Romain of Kanop and explore present techniques combined with ground truth data to produce insights and guidance. Learn about the technical interfaces and patterns to best combine the best of both worlds.

Want to participate and accelerate your understanding?

RSVP for the next session here!