Peat-MOSS (Peatland Mapping and Observation with Satellite Sensors)

泥炭地是最安全的温室气体汇之一，能储存25% of global soil carbon, yet their degradation is responsible for 2-5% of all anthropogenic emissions\[Q1ref-1\]. Understanding the large potential for both storage and emissions, there has been an exponential increase in restoration projects aimed at reducing emissions and enhancing carbon storage in peatlands. However, there is currently no accurate and scalable method for measurement, reporting, and verification (MRV) of peatland restoration projects. At present, the impact of peatland restoration for greenhouse gas reduction (GGR) is simply assumed from a change in peatland classification (e.g., from "drained" to "restored"). Additionally, finding proper sites for further deployment of GGR projects is hindered by the limited knowledge of global peat extent. For example, in tropical regions the total un-mapped peatland area may be three times larger, and four times more voluminous than currently mapped\[Q1ref-2\]. Digital mapping and monitoring of peatlands based on satellite earth observation (EO) data has the potential to scale to meet the global need for accurate MRV and mapping of GGR projects, yet has been limited in three key areas:* Heavy reliance on basic statistical techniques.* Lacking quantification of uncertainty.* Lacking consistency in resolution and data inputs.These limitations have restricted the ability to monitor the effectiveness of peatland projects and identify/prioritise locations for future GGR projects.Sylvera will conquer the limitations of digital peatland mapping and monitoring by combining its expertise in machine learning (ML) and EO data with the research of the UK Centre for Ecology and Hydrology (UKCEH) - leaders in peatland GGR demonstration. Sylvera will lead the next-generation of digital peatland measurements to provide the scalable MRV solution that is desperately needed to bring integrity and confidence to GGR projects. Peat-MOSS will respond by developing an ML-driven method, combining its industry-leading deep-learning models based on EO data with the extensive research from UKCEH. Peat-MOSS will develop maps of peat extent and additional indicators of peat degradation that can be used to determine whether peatlands are emitting or sequestering CO2\. The use cases of Peat-MOSS maps are 1) MRV of peat GGR projects and 2) identification and prioritisation of peatland GGR project sites. Sylvera will leverage EO data and ML technology to provide digital GGR MRV. This MRV solution will ensure the effectiveness, security, and permanence of GGR projects by providing consistent and scalable monitoring of peatlands.

Peatlands are among the most secure sinks for greenhouse gases, storing 25% of global soil carbon, yet their degradation is responsible for 2-5% of all anthropogenic emissions\[Q1ref-1\]. Understanding the large potential for both storage and emissions, there has been an exponential increase in restoration projects aimed at reducing emissions and enhancing carbon storage in peatlands. However, there is currently no accurate and scalable method for measurement, reporting, and verification (MRV) of peatland restoration projects. At present, the impact of peatland restoration for greenhouse gas reduction (GGR) is simply assumed from a change in peatland classification (e.g., from "drained" to "restored"). Additionally, finding proper sites for further deployment of GGR projects is hindered by the limited knowledge of global peat extent. For example, in tropical regions the total un-mapped peatland area may be three times larger, and four times more voluminous than currently mapped\[Q1ref-2\]. Digital mapping and monitoring of peatlands based on satellite earth observation (EO) data has the potential to scale to meet the global need for accurate MRV and mapping of GGR projects, yet has been limited in three key areas:* Heavy reliance on basic statistical techniques.* Lacking quantification of uncertainty.* Lacking consistency in resolution and data inputs.These limitations have restricted the ability to monitor the effectiveness of peatland projects and identify/prioritise locations for future GGR projects.Sylvera will conquer the limitations of digital peatland mapping and monitoring by combining its expertise in machine learning (ML) and EO data with the research of the UK Centre for Ecology and Hydrology (UKCEH) - leaders in peatland GGR demonstration. Sylvera will lead the next-generation of digital peatland measurements to provide the scalable MRV solution that is desperately needed to bring integrity and confidence to GGR projects. Peat-MOSS will respond by developing an ML-driven method, combining its industry-leading deep-learning models based on EO data with the extensive research from UKCEH. Peat-MOSS will develop maps of peat extent and additional indicators of peat degradation that can be used to determine whether peatlands are emitting or sequestering CO2\. The use cases of Peat-MOSS maps are 1) MRV of peat GGR projects and 2) identification and prioritisation of peatland GGR project sites. Sylvera will leverage EO data and ML technology to provide digital GGR MRV. This MRV solution will ensure the effectiveness, security, and permanence of GGR projects by providing consistent and scalable monitoring of peatlands.