This application seeks to address the lack of consistent, scalable, science-based and timely climate and environmental data for farming and land management businesses ("FLMs") and those financial services companies ("FSCs") that support them. New data that captures detailed knowledge of land use, biodiversity and carbon is rapidly becoming essential for risk decision-making and reporting in bank lending and insurance as the UK transitions to new land management subsidy regimes and net zero. Technology Solution The proposed innovative solution will deliver consistent, scalable and science-based data on the climate and environmental credentials of FLMs for multi-faceted uses across FSCs, supporting the changing land management practices that will deliver carbon capture and improved biodiversity. The technology integrates Earth Observation data streams with geographically accurate land parcels and translates this into timely, accessible and relevant data to FSCs, for the purpose of understanding, assessing and acting on the financial risks and opportunities from climate and environmental change. Key FSC use cases (none of which are possible today) include: * enhanced credit risk descisioning, for the c.£20bn market in bank lending to FLMs, that takes account of the shift in land management practices towards habitat restoration and environmentally sustainable land management (and the monetisation potential arising from this) * reliable, science-based quantification and valuation of changes in Natural Capital (e.g. carbon and biodiversity) to underpin insurance and lending security calculations * consistent, accurate disclosure of scope 3 financed emissions and broader net environmental impact from lending to the agricultural and land management sector. Scalability and readiness FLMs are beginning to use drone technology to measure their activities -- crop management, forestry surveys etc. This same technology is used to collect the data necessary to accurately measure carbon and monitor biodiversity, making the digital environmental data output entirely scalable. The foundations of the solution have been developed, including relevant machine learning algorithms for forestry and woodland, a map-based technology platform and a user interface. Work is ongoing to extend capabilities to other habitats. This grant is therefore focused on marrying the foundation technology with financial services use cases that will revolutionise environmental risk management. This application brings together two highly motivated and relevant companies to support the delivery of this proposed solution across what is expected to be the whole of the rural land management enterprise sector and provides the opportunity to create an FLM and FSC environment that together can deliver substantial positive climate and environmental impact.

This application seeks to address the lack of consistent, scalable, science-based and timely climate and environmental data for farming and land management businesses ("FLMs") and those financial services companies ("FSCs") that support them. New data that captures detailed knowledge of land use, biodiversity and carbon is rapidly becoming essential for risk decision-making and reporting in bank lending and insurance as the UK transitions to new land management subsidy regimes and net zero. Technology Solution The proposed innovative solution will deliver consistent, scalable and science-based data on the climate and environmental credentials of FLMs for multi-faceted uses across FSCs, supporting the changing land management practices that will deliver carbon capture and improved biodiversity. The technology integrates Earth Observation data streams with geographically accurate land parcels and translates this into timely, accessible and relevant data to FSCs, for the purpose of understanding, assessing and acting on the financial risks and opportunities from climate and environmental change. Key FSC use cases (none of which are possible today) include: * enhanced credit risk descisioning, for the c.£20bn market in bank lending to FLMs, that takes account of the shift in land management practices towards habitat restoration and environmentally sustainable land management (and the monetisation potential arising from this) * reliable, science-based quantification and valuation of changes in Natural Capital (e.g. carbon and biodiversity) to underpin insurance and lending security calculations * consistent, accurate disclosure of scope 3 financed emissions and broader net environmental impact from lending to the agricultural and land management sector. Scalability and readiness FLMs are beginning to use drone technology to measure their activities -- crop management, forestry surveys etc. This same technology is used to collect the data necessary to accurately measure carbon and monitor biodiversity, making the digital environmental data output entirely scalable. The foundations of the solution have been developed, including relevant machine learning algorithms for forestry and woodland, a map-based technology platform and a user interface. Work is ongoing to extend capabilities to other habitats. This grant is therefore focused on marrying the foundation technology with financial services use cases that will revolutionise environmental risk management. This application brings together two highly motivated and relevant companies to support the delivery of this proposed solution across what is expected to be the whole of the rural land management enterprise sector and provides the opportunity to create an FLM and FSC environment that together can deliver substantial positive climate and environmental impact.

This application seeks to address the lack of consistent, scalable, science-based and timely climate and environmental data for farming and land management businesses ("FLMs") and those financial services companies ("FSCs") that support them. New data that captures detailed knowledge of land use, biodiversity and carbon is rapidly becoming essential for risk decision-making and reporting in bank lending and insurance as the UK transitions to new land management subsidy regimes and net zero. Technology Solution The proposed innovative solution will deliver consistent, scalable and science-based data on the climate and environmental credentials of FLMs for multi-faceted uses across FSCs, supporting the changing land management practices that will deliver carbon capture and improved biodiversity. The technology integrates Earth Observation data streams with geographically accurate land parcels and translates this into timely, accessible and relevant data to FSCs, for the purpose of understanding, assessing and acting on the financial risks and opportunities from climate and environmental change. Key FSC use cases (none of which are possible today) include: * enhanced credit risk descisioning, for the c.£20bn market in bank lending to FLMs, that takes account of the shift in land management practices towards habitat restoration and environmentally sustainable land management (and the monetisation potential arising from this) * reliable, science-based quantification and valuation of changes in Natural Capital (e.g. carbon and biodiversity) to underpin insurance and lending security calculations * consistent, accurate disclosure of scope 3 financed emissions and broader net environmental impact from lending to the agricultural and land management sector. Scalability and readiness FLMs are beginning to use drone technology to measure their activities -- crop management, forestry surveys etc. This same technology is used to collect the data necessary to accurately measure carbon and monitor biodiversity, making the digital environmental data output entirely scalable. The foundations of the solution have been developed, including relevant machine learning algorithms for forestry and woodland, a map-based technology platform and a user interface. Work is ongoing to extend capabilities to other habitats. This grant is therefore focused on marrying the foundation technology with financial services use cases that will revolutionise environmental risk management. This application brings together two highly motivated and relevant companies to support the delivery of this proposed solution across what is expected to be the whole of the rural land management enterprise sector and provides the opportunity to create an FLM and FSC environment that together can deliver substantial positive climate and environmental impact.

This application seeks to address the lack of consistent, scalable, science-based and timely climate and environmental data for farming and land management businesses ("FLMs") and those financial services companies ("FSCs") that support them. New data that captures detailed knowledge of land use, biodiversity and carbon is rapidly becoming essential for risk decision-making and reporting in bank lending and insurance as the UK transitions to new land management subsidy regimes and net zero. Technology Solution The proposed innovative solution will deliver consistent, scalable and science-based data on the climate and environmental credentials of FLMs for multi-faceted uses across FSCs, supporting the changing land management practices that will deliver carbon capture and improved biodiversity. The technology integrates Earth Observation data streams with geographically accurate land parcels and translates this into timely, accessible and relevant data to FSCs, for the purpose of understanding, assessing and acting on the financial risks and opportunities from climate and environmental change. Key FSC use cases (none of which are possible today) include: * enhanced credit risk descisioning, for the c.£20bn market in bank lending to FLMs, that takes account of the shift in land management practices towards habitat restoration and environmentally sustainable land management (and the monetisation potential arising from this) * reliable, science-based quantification and valuation of changes in Natural Capital (e.g. carbon and biodiversity) to underpin insurance and lending security calculations * consistent, accurate disclosure of scope 3 financed emissions and broader net environmental impact from lending to the agricultural and land management sector. Scalability and readiness FLMs are beginning to use drone technology to measure their activities -- crop management, forestry surveys etc. This same technology is used to collect the data necessary to accurately measure carbon and monitor biodiversity, making the digital environmental data output entirely scalable. The foundations of the solution have been developed, including relevant machine learning algorithms for forestry and woodland, a map-based technology platform and a user interface. Work is ongoing to extend capabilities to other habitats. This grant is therefore focused on marrying the foundation technology with financial services use cases that will revolutionise environmental risk management. This application brings together two highly motivated and relevant companies to support the delivery of this proposed solution across what is expected to be the whole of the rural land management enterprise sector and provides the opportunity to create an FLM and FSC environment that together can deliver substantial positive climate and environmental impact.

The Covid-19 pandemic has accentuated the Climate Emergency and the need for a Green Recovery, accelerating the requirement for the business world to de-carbonise and become more environmentally sustainable; whilst also enabling landowners to transform their agricultural and land management practices. Climate Solutions Exchange Ltd (CS-Ex) aims to break down the current barriers to entry and democratise the voluntary carbon markets, by enabling the accurate and affordable measurement of carbon sequestration, rather than the costly processes and systems currently in place, which are based on models and assumptions. CS-Ex's aim is to significantly increase quantities of carbon brought to the voluntary market and help satisfy the increasing demand for carbon offsetting. Through the use of technology, CS-Ex intends to turn carbon offsetting MRV from 'Monitoring, Reporting & Verification' into '_MEASUREMENT_, Reporting & Verification'. The project will achieve this by setting up 'Carbon Observatory' sites at woodland planting, regenerative farming and peatland restoration projects in the UK. The sites will have their carbon levels measured and calibrated by satellite and drone Earth Observation (EO), machine learning (ML), and ground based measurements techniques. By successfully measuring carbon, CS-Ex intends to enable: the measurement, monitoring and audit of land managers' Natural Capital production; the sale of measured carbon; and the planning of wider Natural Capital interventions. Reacting to the recent Covid-19 pandemic, key drivers of this project are: the latent opportunities presented by the potential 'circular carbon economy' that can assist the rural sector in recovering from the Covid-19 pandemic with new income streams from Natural Capital payments; establishing new highly skilled jobs in remote sensing EO technologies; and to de-risk the potential impact of a second Covid wave by enabling remote sensing technology to deliver the monitoring results needed without the need for significant people movement between survey sites.