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Satellite based Environmental risk analysis tool - FinEO

Satellite based Environmental risk analysis tool - FinEO
基于卫星的环境风险分析工具 - FinEO
批准号:
10030702
负责人:
金额:
$5.54万
依托单位:
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
地球观测数据集有助于深入了解与土地利用变化相关的不同类型的自然和生物多样性风险、影响和机遇:生态系统退化的归因(程度和质量);监测保护区内或周围的经济活动或遵守环境条例的情况;识别和监测自然恢复投资机会。Telespazio UK提议开发一种基于卫星的人工智能时空工具,称为FinEO,该工具从不同的传感器摄取卫星图像,光学、雷达和热成像;与特定行业活动相关的数据集和环境保护数据集。该工具将支持对土地和水环境变化的精细监测,这些变化可能与工业活动有关,以解决自然资本退化和/或恢复问题,从而进行环境风险评估。主题作为解决方案,旨在披露整个行业活动的环境影响,并为金融机构创建数据和分析,以提高其内部评分,风险评估机制。该服务还将有助于解决围绕气候相关诉讼索赔的诉讼风险主题,因为它可以在使用观测数据集和变化分析的资产级别透明度和披露验证工具方面发挥重要作用。
英文摘要
Earth observation (EO) datasets provide insights into different types of nature and biodiversity risks, impacts and opportunities linked to land use changes: attribution of ecosystem degradation (extent and quality) to its economic actors or drivers; monitoring of economic activity in or around protected areas or compliance with environmental regulations; identification and monitoring of nature restoration investment opportunities.Telespazio UK proposes to develop a satellite based AI Spatio- temporal tool called FinEO that ingests satellite imagery from different sensors - optical, radar and thermal; datasets associated to specific industry activities and environmental conservation datasets. The tool will support granular monitoring of changes in the land and water environment that can be associated to industry activities to address natural capital deterioration and/or restoration for environmental risk assessment.FinEO will address the **Impact Disclosure** theme as the solution aims to work on disclosing environmental impacts across industry activities and create data and analytics for financial institutions to improve their internal scoring and risk assessment mechanisms. The service will also help to address the theme of Litigation risks around climate related litigation claims as it can play a vital role in being a tool of transparency and disclosure validation at the asset level using observational data sets and change analysis.
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