FOSS4G 2022 general tracks

Momen Mawad

QGIS Enthusiast, Data Science follower, Web design lover and anything else related to computer development.

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Sessions

08-25
12:30
30min
Developing a pilot method to measure biodiversity related financial risk at financial portfolio level using Earth Observation and other spatially explicit data
Hinrich Paulsen, Momen Mawad

Humanity is facing a number of challenges, among which climate change and biodiversity loss range in top positions. Investors are exposed to those risks through their investee companies given their dependence on biodiversity and ecosystem services. Therefore, just recently the financial community has started to pay attention to the economic and financial consequences of biodiversity loss. However, a key challenge is that a conceptual framework for measuring and understanding biodiversity-related financial risks (physical and transition risks) is less advanced than for climate-related financial risks. Thus the topic of biodiversity and corresponding risks is gaining momentum and methodologies how to assess them are being developed. In this context and due to the mounting pressure of biodiversity loss numerous frameworks like the EU Taxonomy for sustainable activities or the Task Force on Nature related Financial Disclosures (TNFD) have recently been created that try to curb these effects at scale. The intention of the international community is to channel investments to business ventures that do not harm biodiversity or ideally even regenerate it while investors are generally interested in minimizing their risks. To this end a consortium of financial specialists, biodiversity experts and remote sensing data analysts is developing a methodology and prototypical platform, initiated by WWF Switzerland, that quantifies the physical risks, i. e. risks associated with degrading ecosystem services (at the site level subject to data availability). Part of the innovation is to quantify ecosystem service dynamics at asset locations, i. e. the locations where companies actually produce their goods. The production sites and related activities are analyzed with regard to their dependency on five ecosystem services, namely (i) surface water, (ii) flood and storm protection, (iii) pollination, (iv) fiber & other materials and (v) climate regulation to quantify the physical risk at these locations by means of an index. This presentation focuses on the physical risk module, where EO data products represent a valuable source of information. The module builds on fundamental work done in the ENCORE project, in which the relationships between drivers of environmental change, natural capital assets, ecosystem services and production processes have been described exhaustively for the entire economy. Additionally, established databases containing information on the status of natural capital assets, e.g. the WRI Aqueduct 3.0 dataset on the spatial distribution of water-related risks, are used as a baseline against which other data can be compared. Up-to-date EO data products are then used to assess drivers of environmental change to investigate dynamics and trends, and to identify potential threats to the natural capital assets and the provisioning of corresponding economy-relevant ecosystem services. Here, we focus on drivers responsible for biodiversity loss, for example by using annual global land cover data from the Copernicus Global Land Service to assess habitat modification due to land cover change.

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