Please describe your proposed solution.
The urgent need for sustainable solutions is driving a rapid adoption of smart environmental monitoring and diagnostics technologies that utilise spaceborne Earth Observation (EO) and climate data. Target applications encompass a wide range of commercial domains, such as natural resource management, disaster management, weather forecasting, precision agriculture, forestry, mineralogical prospection and global trade. Furthermore, the emerging market for carbon credits and other sustainability services, such as direct carbon capture, regenerative agriculture, reforestation and afforestation require careful monitoring and validation to achieve the desired level of credibility and trust.
Unfortunately however, multiple major technological bottlenecks continue to impede wide adoption and commercial utility of environmental sensing technologies beyond the limited scope of scientific research. We have conducted an extensive survey of multiple organisations that aim to promote and accelerate reforestation, afforestation and soil carbon restoration, including for example Open Forest Protocol (<https://www.openforestprotocol.org/>), Restore (https://restor.eco), The Pond Foundation (<https://thepondfoundation.org/>), Landano (<https://www.landano.io/>), Forest Conservation Fund (<https://www.fundforests.org/>) and Agora Carbon Alliance (https://agorocarbonalliance.com).
Our findings show that at this time the vast majority of monitoring and validation for such projects relies on labour-intense, expensive, time-consuming and often unreliable ground samples and manual inspection. Significant efforts have been invested into automation of monitoring and validation using remote sensing technology, but the scalability and efficiency of such methodology is currently limited by the following factors:
- Commercial high-resolution EO imagery is far too expensive for most environmental monitoring projects and applications, while the spatial resolution of the low-cost EO imagery is too coarse for most such applications.
- Challenging atmospheric conditions, such as obstruction by clouds and cloud shadows, make the availability of high-quality data highly irregular and temporarily incoherent.
- Monitoring often requires high-quality historical imaging data that is often unavailable, or too expensive.
- Each EO system is designed to address a specific segment of use cases using a specific combination of technical characteristics, such as revisit time, number of spectral bands, spectral range and spatial resolution, thus making automated assimilation of data from multiple such systems difficult, or impossible.
- Radiometric calibration, and thus the stability and reliability of collected data varies drastically between different systems and continues to present a major and largely unsolved technological challenge.
Significant attention has been recently raised by the Dynamic World by Google (https://www.dynamicworld.app/) – “A near real-time land cover dataset for our constantly changing planet”. This system clearly demonstrates the immense potential of remote sensing for environmental monitoring applications. The system addresses the very important challenge of global coarse land-cover classification into nine major types, however it does not provide the means to understand the local environmental dynamics for a specific project or use case.
Our vision
The proposed project will develop and deploy an Satellite Oracle that will offer a consolidated source of regularised multi-modal multi-scale (spatial, spectral and temporal) environmental data required for implementation of low-cost, scalable monitoring and validation solutions for carbon capture and ecological restoration projects and DApps. The proposed data structure will include a fusion of spatial, spectral and temporal features specifically designed and optimised for training of analytical and predictive ML models.
The information aggregated by Satellite Oracle will act as a form Environmental Passport for any target plot of land that will both record all changes of status, as well as provide a source of objective data for the analysis of dynamics, performance and health indicators.
Figure 1. H3: Uber’s Hexagonal Hierarchical Spatial Index
The proposed Satellite Oracle will utilise Uber’s Hexagonal Hierarchical Index (H3) for multi-scale indexing and access to consolidated environmental data. The system will provide access to the following data types in the form of regularised and consolidated multi-layer multi-modal data cubes:
- Instant
- Radiometrically calibrated, cloud-free multi spectral satellite imaging data at 1m/px spatial resolution
- Short-term cycle – 12-month time series at 5 days revisit rate
- Reflectance spectrum
- Climate data
- Temperature (max/min/5-day average)
- Precipitation (5-day average)
- Cloud cover (5-day average)
- Long-term cycle – 12-year time series at 60 days revisit rate
- Vegetation index
- Climate data
- Temperature (max/min/60-day average)
- Precipitation (60-day average)
- Cloud cover (60-day average)
Figure 2. Ecomandala visualisation of the information features constituting the Satellite Oracle multi-modal spatial-spectral-temporal dataset.
The resultant consolidated source of environmental data will be deployed on Cardano blockchain and will be made available through a standardised API which will significantly streamline and simplify access to such data for developers of environmental monitoring and validation applications, as well as a wide variety of sustainability focused DApps. Some examples of such DApps could include DeFi support of regenerative agriculture, agriculture supply chains, forest conservations and tree planting projects.
As part of our future work, we are planning the development and release of an Ecomandala NFT that is a dynamic visualisation of the aggregated and regularised environmental data detailed in Figure 4. Ecomandala will represent the historical record and the current state of any given plot of land in an information-rich and visually compelling form allowing for interactive and engaging exploration of environmental data.
Figure 3. Original Sentinel-2 L2A scene (left) and processed scene with the clouds and cloud shadows removed using the proposed data fusion method (right).
The proposed project will invoke the latest developments in the area of Artificial Intelligence and Machine Learning to enable coherent fusion of multiple sources of environmental data, including European Space Agency (ESA) Copernicus Sentinel 1 and 2, as well as the corresponding climate data in order to obtain regularised, cloud and cloud shadow-free time series of satellite imaging data.
The satellite imaging data will be further super-resolved to the spatial resolution of 2 m/px, significantly expanding the range of target monitoring and verification applications.
Figure 4. x10 super-resolved images generated by Gamma Earth S2DR model. Sentinel-2 RGB 10 m/px (left), S2DR RGB 1 m/px (center) and Google Maps RGB 30 cm/px (right).
For more information on Sentinel-2 Super-Resolution please see here: https://medium.com/@ya_71389/sentinel-2-deep-resolution-2-0-c3d530d9bdf8
How does your proposed solution address the challenge and what benefits will this bring to the Cardano ecosystem?
The envisioned Satellite Oracle will help resolve multiple major technological bottlenecks associated with the challenge of sourcing, accessing and processing relevant environmental data required for monitoring, auditing, and validation of carbon capture, ecological protection and restoration projects. It will enable the development and deployment of a new class of high impact DApps on Cardano blockchain positioning Cardano as a platform of choice for in environmental monitoring, reporting and verification (MRV) applications.
Satellite Oracle will constitute a platform and an integration layer enabling further development and deployment of monitoring and validation solutions for specific DApps on Cardano ecosystem. We therefore inspire to
- Showcase the methodology of low-cost scalable monitoring and validation of ecological restoration projects
- Standardize, streamline and simplify access to consolidated environmental data
- Attract the developers of monitoring and validation solutions for carbon capture and ecological restoration projects to Cardano ecosystem
Our solution will further promote collaboration, synergy and interoperability between Cardano projects by leveraging the achievements of the recent Fund 8 “Oracle Development Portal” project: https://cardano.ideascale.com/c/idea/400771 (which is not a related project but we will be happy to collaborate in order to maximise the impact of both projects).
Examples of funded and submitted Cardano Ideascale projects with direct synergy potential to the proposed Satellite Oracle
- Decentralised digital field boundary repository https://cardano.ideascale.com/c/idea/107444
- 21st century Agri supply chain https://cardano.ideascale.com/c/idea/403695
- Oracle Developer Portal https://cardano.ideascale.com/c/idea/400771
- Indigenous Land Rematriation https://cardano.ideascale.com/c/idea/398750
- Open ledger for agricultural land https://cardano.ideascale.com/c/idea/400812
- Protecting wildlife & Maasai, Kenya https://cardano.ideascale.com/c/idea/399158
- Landano: Cardano land registry Dapp https://cardano.ideascale.com/c/idea/381957
- Community validation Dapp https://cardano.ideascale.com/c/idea/421218
How do you intend to measure the success of your project?
The team has established several key metrics and indicators to measure the success of the project. These metrics are aligned with the project's goals and objectives and serve as benchmarks for evaluating its effectiveness as follows:
- Accuracy and Performance: One of the primary measures of success for the Satellite Oracle project is the accuracy and performance of the system
- User Feedback and Satisfaction: The team will actively gather feedback from users of the Satellite Oracle platform
- Adoption and Engagement: The level of adoption and engagement with the Satellite Oracle platform will serve as an important measure of success
- Impact on Decision-Making: The team aims to assess the project's impact on decision-making processes related to environmental issue
- Collaboration and Partnerships: The team will measure the success of the project by evaluating its ability to foster collaboration and partnerships with relevant stakeholder
- Academic Recognition: The team intends to measure the success of the project through academic recognition and contribution to the scientific community
- Long-Term Sustainability: The team will assess the project's long-term sustainability by evaluating its ability to maintain and improve the Satellite Oracle platform beyond the initial implementation phase
By regularly monitoring and evaluating these metrics throughout the project's lifecycle, the team will be able to assess the success and impact of the Satellite Oracle project and make necessary adjustments and improvements as needed.
Please describe your plans to share the outputs and results of your project?
The team has devised a comprehensive plan to share the outputs and results of the project with various stakeholders. The key aspects of the sharing plan are as follows:
- Web-based Platform: The Satellite Oracle will have a dedicated web-based platform where users can access the system's outputs and result
- Stakeholder Engagement: The team recognises the importance of engaging with stakeholders throughout the project
- Media and Communications: The team will leverage various media and communication channels to disseminate the project's outputs and results to a broader audience
- Collaboration and Partnerships: The team will actively seek collaboration and partnerships with relevant organisations, institutions, and initiative
- Documentation and Reports: The team will prepare comprehensive documentation and reports summarising the project's outputs, findings, and recommendation
- Open Source: The platform will be realised as open source to the community including access API, web platform, blockchain integration and oracle implementation. Please note that some of the core background IP including the super-resolution, cloud removal and other analytical models will not be open-sourced.
By employing a multi-faceted approach that includes a dedicated web platform, stakeholder engagement, media and communications, collaboration and partnerships, and comprehensive documentation, the team aims to effectively share the outputs and results of the project with a wide range of stakeholders.