LeafTrack is a remote sensing service that utilizes free, high-resolution satellite images to monitor the vegetation layer of a given area, such as a nature reserve. The service provides detailed information about the vegetation, including its health, growth, and distribution, through the use of advanced algorithms and machine learning models.
This information is then stored in a blockchain-based system, which ensures its immutability and transparency. The blockchain system also allows for secure and decentralized data sharing among relevant stakeholders, such as researchers and conservationists.
By leveraging this technology, LeafTrack acts as an early warning system for any changes in the vegetation layer, enabling reserve managers to make well-informed decisions in a timely manner. This can include identifying areas that require more attention or intervention, such as those affected by invasive species or climate change
Specific bugs or hurdles that we encountered in the LeafTrack project include issues with satellite image processing, inaccuracies in machine learning models, and security vulnerabilities in the blockchain-based system.
These challenges was addressed through rigorous testing and continuous improvement of the system's components.