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  • AI Forest Monitoring: How DeepForest Works

    AI Forest Monitoring: How DeepForest Works

    AI forest monitoring can help us understand what is happening across large forest areas without relying solely on on-the-ground inspections.

    That is one of the ideas behind DeepForest, a Vottun platform that combines artificial intelligence, satellite imagery and blockchain to automate the monitoring of forests and reforestation projects.

    Our goal is to turn large volumes of territorial data into useful, continuous and verifiable information that can help us better understand how forests evolve over time.

    Turning satellite imagery into useful information

    Monitoring large forest areas is not a simple task.

    Traditional approaches rely heavily on field visits, periodic measurements and processes that can become costly and difficult to maintain when projects need to be monitored for years or even decades.

    DeepForest can define forest plots using geographic coordinates and periodically analyze satellite imagery captured over those areas. The system then uses artificial intelligence to process different parameters and extract information about the condition and evolution of vegetation.

    In this way, we can transform images of the territory into information that helps us understand what is happening on the ground and identify changes that may require attention.

    AI forest monitoring to detect change

    Artificial intelligence is one of the core components of DeepForest.

    The models developed for the platform can automatically analyze satellite imagery, detect changes in vegetation cover and identify conditions that may require action.

    The platform achieves more than 90% accuracy in vegetation-cover detection and can identify issues such as drought, wildfires or pests 50% faster than conventional methods.

    This AI forest monitoring approach creates the foundation for a more continuous model, reducing the need to wait for the next field inspection before obtaining updated information about a specific area.

    Blockchain for data integrity and traceability

    Collecting data is only part of the challenge.

    For reforestation, sustainability and emissions-offset projects, it is also important to establish what information was generated, when it was generated and to preserve its integrity over time.

    This is where blockchain comes in.

    DeepForest stores monitoring results in a database protected with blockchain technology, adding another layer of integrity and traceability to the information generated throughout the monitoring process.

    The three technologies work together in a straightforward flow:

    Satellite → Artificial Intelligence → Blockchain

    Satellites observe the territory, AI interprets the data and blockchain helps preserve the traceability of that information.

    Monitoring designed for the long term

    Time is one of the biggest challenges in forest and reforestation projects.

    A reforestation project does not end when trees are planted. Vegetation needs to be monitored as it develops, potential issues need to be identified and progress may need to be verified over long periods.

    This is particularly relevant for emissions-offset projects, where commitments involving reforested areas can extend for decades.

    DeepForest is designed to make this process easier by generating information periodically and maintaining a verifiable historical record of how each monitored plot evolves. In this way, AI forest monitoring can complement field work with updated and traceable information.

    Technology applied to a real-world problem

    For us, DeepForest also represents how technologies such as artificial intelligence and blockchain should be applied.

    The goal is not to use technology for its own sake. It is to combine different technologies when each one solves a specific part of a real problem.

    Satellite imagery helps us observe.

    Artificial intelligence helps us interpret.

    Blockchain helps us add traceability.

    Together, they provide a new way to monitor how forests evolve and manage the information generated throughout that process.

    A project developed with the support of ACCIÓ

    DeepForest has been developed with the support of ACCIÓ, the Government of Catalonia’s agency for business competitiveness, through its grant program for business R&D projects focused on climate change, funded by the Catalan Climate Fund.

    The project has received €173,546 through this program.

    This support has helped us continue developing and validating technology designed to apply digital innovation to a very tangible challenge: improving how we understand, monitor and protect forest ecosystems.

    At Vottun, we would like to thank ACCIÓ for supporting projects that put technology to work on real-world challenges and for helping bring greater visibility to DeepForest.

    DeepForest is gaining visibility

    Over the past few days, several media outlets have covered DeepForest and the work we are doing at Vottun.

    The project has been featured by Diari de Catalunya, Diario PYME and ON ECONOMIA / El Nacional, in addition to the institutional announcement from the Government of Catalonia.

    The growing external visibility around the project gives us another opportunity to explain not only what we are building, but why we are building it.

    DeepForest continues to move forward as our approach to applying AI forest monitoring to real-world forest management challenges.

    We will keep exploring how the combination of artificial intelligence, satellite imagery and decentralized technologies can provide new tools to better understand what is happening in our forests and help protect them.

    From satellite to ground. From data to better-informed decisions.

    Learn more and media coverage