Integrating digital Earth Observation environmental data into financial services decision making

该应用程序旨在解决农业和土地管理企业（“flm”）以及支持它们的金融服务公司（“fsc”）缺乏一致、可扩展、基于科学和及时的气候和环境数据的问题。随着英国向新的土地管理补贴制度和净零过渡，获取有关土地利用、生物多样性和碳的详细知识的新数据正迅速成为银行贷款和保险风险决策和报告的关键。技术解决方案拟议的创新解决方案将提供一致的、可扩展的、基于科学的flm气候和环境凭证数据，用于fsc的多方面用途，支持不断变化的土地管理实践，从而实现碳捕获和改善生物多样性。该技术将地球观测数据流与地理位置准确的地块相结合，并将其转化为fsc及时、可获取和相关的数据，以便了解、评估气候和环境变化带来的金融风险和机遇，并采取行动。关键的FSC用例（今天都不可能）包括：*提高信用风险决策，为200亿英镑的银行贷款市场向flm提供贷款，考虑到土地管理实践向栖息地恢复和环境可持续土地管理的转变（以及由此产生的货币化潜力）*可靠，对自然资本（如碳和生物多样性）的变化进行基于科学的量化和评估，以支持保险和贷款担保计算*，一致、准确地披露第3类融资排放以及向农业和土地管理部门提供贷款所产生的更广泛的净环境影响。可扩展性和准备性flm开始使用无人机技术来衡量他们的活动——作物管理、林业调查等。同样的技术也被用于收集精确测量碳和监测生物多样性所需的数据，使数字环境数据输出完全可扩展。解决方案的基础已经开发出来，包括林业和林地的相关机器学习算法、基于地图的技术平台和用户界面。将能力扩展到其他栖息地的工作正在进行中。因此，这笔赠款的重点是将基金会技术与金融服务用例结合起来，这将彻底改变环境风险管理。该申请汇集了两家高度积极和相关的公司，以支持该解决方案在整个农村土地管理企业部门的交付，并提供了创建FLM和FSC环境的机会，这些环境可以共同产生实质性的积极气候和环境影响。

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 SolutionThe 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 readinessFLMs 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.