For ecological research as well as for GAIA use cases, it is necessary to reliably and accurately recognise the behaviour of different animal species over a long period of time in remote wilderness regions. To do this, GAIA scientists have developed and trained an artificial intelligence (AI) that can perform behavioural classification from GPS and acceleration data and tell us exactly what, for example, white-backed vultures fitted with animal tags are doing at any given time and place. This AI will eventually run directly on the GAIA animal tags and generate behavioural information from sensor data. In a second step, the scientists combined the behaviour thus classified with the GPS data from the tags. Using algorithms for spatial clustering, they identified locations where certain behaviours occurred more frequently. In this way, they obtained spatially and temporally finely resolved locations where vultures fed. Last but not least, GAIA is developing an AI for image recognition that will analyse photos taken by the integrated camera of the new tag system. All those algorithms will run directly on the tag and can perform efficient embedded data processing. This also places very special demands on image recognition AI, which must operate particularly sparingly and with small amounts of data. To this end, GAIA teams are developing appropriate strategies and models for sparse AI.

Satellites and aircrafts play a crucial role in gathering environmental data from the distance, helping us to better understand our climate and ecosystems. Remote sensing, often conducted from aircraft, balloons, or satellites, allows us to monitor large areas and remote regions over extended periods. These “eyes in the sky” are invaluable complements to land-based observations, helping us understand ocean and air currents, land cover changes, and climate change. However, animals also possess extraordinary senses and a unique ability to detect changes in their habitats. By combining animal capabilities with remote sensing technologies, GAIA aims at enhancing our ability to monitor and understand our planet. Animals have superior sensory abilities and behavioural strategies that enable them to sense subtle and dramatic changes in their ecosystems, as well as to detect critical incidents. Vultures, for example, act as “sentinel species” and can elevate the concept of remote sensing to new heights. They regularly patrol vast areas in search of food, operating without emissions, additional resources, or repairs. Furthermore, their patrols are guided by their exceptional vision and the mission to find carcasses. The way they patrol, what they search for, and the incidents they lead us to may be linked to specific environmental changes and ecological events.

To fully exploit the potential of vulture-borne remote sensing, GAIA focuses on two essential aspects. Firstly, powerful tracking devices are attached to vultures to monitor their movements and behaviour on detailed temporal and spatial scales. Secondly, new technological solutions are being developed to better understand what the animals observe and do. This includes a newly developed camera tag featuring an integrated camera, artificial intelligence algorithms for behaviour detection and image recognition, and satellite uplink for real-time coverage in remote regions. With these tools, animals can capture imagery and provide data of their surroundings faster, with higher resolution and specificity than satellite imagery. This innovative approach allows us to see nature through the eyes of animals.

The forestry sector is suffering from corruption and is limiting benefits for local and Indigenous communities. Our solution allows local communities to tackle forest illegalities and land rights violations and at the same time to secure their land rights and economic rights over forest resources by monitoring and protecting their territory, reinforcing sustainable development and autonomy.  Data collected through the tool also supports judicial or non-judicial cases when local and indigenous communities suffer human rights abuses. 

Having data collected and analysed through a digital tool is an innovation, although to foster changes and ensure local communities and Indigenous people's protection and sustainable lifestyle the data is used for law enforcement and advocacy purposes. To this end, strong local, national and international advocacy networks are needed to take action against reported abuses and to achieve policy changes. By enabling information to be shared between users and opening up data to the general public, the tool facilitates collaborative working. 

Our solution is based on a digital tool whose goal is to collect and facilitate the analyse of the data sent by community observers and our partners. This tool's efficiency relies on the fact that it is digital, easy to use and low costs for local and Indigenous communities. It enables us to work with hard-to-reach areas around the world, to have quantitative data to support national and international advocacy and to get supporting evidence for legal cases. The adaptability of our solution also lies in the fact that it can be used to monitor a variety of issues (illegal logging - artisanal or industrial, mining, carbon market projects' impact, GBV, etc.), in a variety of contexts.  

The evidence is building that granting Indigenous peoples and other local communities' control over their territories improves forest protection. This is because they are directly invested in the survival of forests and want to ensure that future generations can continue to live and thrive in them. Yet a lot of development and environmental and climate-related programs are not created in collaboration with the people who will be impacted by them. Therefore, our solution arose from the challenges that grassroots organisations and Indigenous and local communities brought to our attention. Those communities are the ones living all the forests illegalities and land tenure violations therefore by directly tackling their challenge it ensures the solution to be genuine and efficient. Working with them directly helps us to better understand the contexts they are facing and adapt the tool in consequence. 

This building block highlights the importance of aligning economic incentives with ecosystem conservation. NFTree increases the opportunity cost of deforestation by providing financial rewards for preserving forests. By connecting private-sector funding to biodiversity-rich carbon sinks, NFTree ensures that conservation becomes a competitive and sustainable land-use option. The integration of digital tools and financial mechanisms creates a model where ecological preservation supports both environmental and economic resilience.

This building block utilizes advanced technology to monitor, report, and verify (MRV) conservation outcomes. The MRV system integrates satellite imagery, artificial intelligence, and on-ground data to measure carbon stocks, forest productivity, and biodiversity in the Andean Chocó. This robust system provides high-resolution data to validate the ecological impact of conservation efforts, ensuring transparency and attracting high-integrity climate financing.

This building block introduces the tokenization of conservation efforts using blockchain technology. NFTree tokenizes 10x10 meter plots of conserved or restored forest land, creating unique digital assets that represent carbon sequestration and biodiversity credits. These tokens are purchased by individuals and companies to offset their carbon footprints, with funds directly channeled to local conservation initiatives. The blockchain ledger ensures transparency, traceability, and accountability in transactions, making conservation efforts more attractive to investors and contributors.

This building block establishes decentralized governance structures using a DAO (Decentralized Autonomous Organization). It ensures transparent and equitable distribution of conservation funds to local land stewards while empowering them with decision-making authority. The DAO model integrates community members into governance, enabling scalable and bottom-up landscape management that complements top-down conservation initiatives