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Integrating digital Earth Observation environmental data into financial services decision making

Integrating digital Earth Observation environmental data into financial services decision making
将数字地球观测环境数据纳入金融服务决策
批准号:
10031337
负责人:
金额:
$6.06万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

项目摘要

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中文摘要
翻译
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,获取土地利用、生物多样性和碳的详细信息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关于FLM气候和环境证书的一致、可扩展和基于科学的数据,用于FSC的多方面用途,支持不断变化的土地管理实践,以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上准确的地块相结合,并将其转化为FSC及时,可访问和相关的数据,以了解,评估气候和环境变化带来的金融风险和机遇,并采取相应行动。(今天没有一个是可能的)包括:* 加强信贷风险决策,为约200亿英镑的银行贷款市场提供FLM,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)* 对自然资本的变化进行可靠的、基于科学的量化和估值(如碳和生物多样性),以支持保险和贷款担保计算 * 一致,准确披露范围3资助的排放量以及向农业和土地管理部门贷款对环境产生的更广泛的净影响。可扩展性和就绪性FLM开始使用无人机技术来衡量其活动--作物管理,该技术还用于收集准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,包括用于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。目前正在努力将能力扩展到其他生境。因此,该赠款的重点是将基础技术与金融服务用例相结合,从而彻底改变环境风险管理。该应用程序将两家积极性很高的相关公司聚集在一起,以支持在整个农村土地管理企业部门提供拟议的解决方案,并提供机会创建一个FLM和FSC环境,对气候和环境产生重大积极影响。
英文摘要
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.
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