Impact Labs 4 Earth partnered with PUR, a global leader in nature-based solutions, to pioneer the next generation of Nature-based Solutions (NbS), by leveraging the latest technological innovations for natural resources monitoring. As stakeholders’ expectations for transparency are rising, Nature-Based Solutions need to constantly improve data quality and direct field observation capabilities. This is in line with the predicted path of the Voluntary Carbon Market (VCM) towards data-driven, higher quality NbS projects.

Over the past decade, remote sensing-based technologies combined with the rise of AI for nature applications paved the way for the digitalisation of NbS monitoring, from pre-planting feasibility studies to Monitoring, Reporting and Verification (MRV). There has been more and more data publicly available from satellites dedicated solely to Earth observation, such as the European Space Agency (ESA) fleet of Sentinel satellites and commercial providers of satellite imagery, which is becoming more accessible through lowered prices.

However, to ensure high quality of RS-based estimations fuelled by AI, the access to  “ground-truth data” is instrumental – field data collected locally, to calibrate and train AI and ML models. As a project developer, PUR has direct privileged access to a wide range of lands, complemented by strong internal knowledge on carbon and forestry science built over almost 20 years of field work. PUR has built close relationships with farmers’ cooperatives in over 30 countries and is on a mission to deliver socio-economic benefits directly to these communities. RS technologies are a key ally to complement traditional field work by capturing a vast amount of data, continuously and at scale.

The PUR digital transformation journey

PUR is embarked in a Digital Transformation Journey, supported by Impact Labs. Part of this evolution consisted in testing RS capabilities to increase efficiency and transparency across the whole project life cycle, starting with a focus on agroforestry projects. PUR is testing different combinations of spatial imagery and AI modelling to leverage RS for a range of critical use cases: from deforestation alerts to biomass estimation. The first project has been developed in partnership with Skylab, a German RS company specialised in precision forestry. In this R&D project, Skylab, PUR and Impact Labs implemented an iterative approach to compare sensors’ capabilities to model vegetation and estimate biomass.

We supported PUR in the business Use Case definition and the RS partner selection, implementing a Request for Proposal and browsing through 40+ companies all over the world. Throughout the project, Impact Labs helped translate tech findings into business insights, to fuel PUR’s renewed data-driven business model. 

Impact Labs provided support for PUR during this process, leveraging internal RS expertise. We thoroughly evaluated Remote Sensing companies in order to select the most appropriate players and solutions to deliver the expected results. With specialised insight on the junction between sustainability and tech, Impact Labs advised PUR on how to excel at data-driven nature-positive impact. This process involved project management on Impact Labs part, working closely with PUR, Skylab and other stakeholders to deliver the results.

Constraints & benefits

Remote Sensing-based biomass estimation is not widely accepted by Certification Bodies due to the hardships in guaranteeing high-accuracy estimates. The models used are often proprietary and thus lack auditability, which is essential for transparency and credible claims.  Additionally, the data collection at local level needs to be based on rigorous procedures to guarantee high quality results, creating a strong dependency between the result of the biomass estimates and the quality and amount of ground-truth data.  

Earth observation from satellites and UAV has been highly useful for global climate change and environmental research since they can provide a thorough analysis of biological, physical, and chemical parameters. Additionally, multi-temporal Earth observation data enables the analysis of large-scale processes and features that are not seen through traditional, ground-based methods. For project developers such as PUR, remote sensing applications respond to multiple use cases with varied degrees of tech maturity.

Benefits for Operations

As demonstrated in the table below, the use of RS can add benefits to PUR’s operations, from the selection of parcels for NbS projects to biomass estimation. Overall, RS enriches the available data, both in quantity and quality, as well as potentially improving the performance of environmental science models. It also contributes to faster anomaly detection and more efficient monitoring of resources. RS can provide a more accurate and potentially cost-effective way to capture the complex local realities and stimulate transparency, by using RS imagery in official communications.

Benefits for PUR’ Stakeholders

Cooperatives of Farmers

PUR highly values its relationship with local communities of farmers that enable the success of nature conservation while also benefiting with socio-economic and local environmental co-benefits. Digital technologies enable more efficient collaboration with local communities by using tools that connect specialists with local participants. Additionally, RS technologies can drastically reduce the labour intensity of local data collection and help to valorize the contribution these players have to the success of NbS projects. 

PUR’s Clients

For PUR’s clients, the collection of enriched data through the whole project lifecycle can be an added tool for decision making. It also improves client reporting, enabling the client to have a more complete picture of what goes on in the field. In this case, the client can have frequent reports that enable them to back up their environmental claims with robust third-party data. 

Laima Barros

Laima Barros

Junior Sustainability Consultant

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