OEMC project use case: Planet health index
Description
There is a growing need to understand the inter-relationships between our atmosphere, the biosphere, and what we could call the anthroposphere. These interactions are complex and not always evident, complicating their analysis through a traditional modelling framework. On the other hand, we do have large amounts of climatic and environmental data in the form of spatio-temporal layers, along with socio-economic data expressing human behaviour, which could be combined in a data-driven perspective. Past work has shown that it is possible to summarize the state of the terrestrial biosphere in a few dimensions by applying statistical techniques to Earth system data cubes. Similarly, socio-economic development data can be statistically reduced to some key dimensions. In this work, the aim is to unify such concepts in a 3-way to derive what we would call: a planet health index (PHI). This index is composed of three separate interpretable axes, each representing one of the domain "spheres" of interest (atmosphere, biosphere and socio-economy). The resulting framework should allow one to identify how one sphere affects another for a given country during a given time frame. This tool is designed to be flexible and allow integration with other data sets, including financial and macroeconomic data, to identify vulnerabilities in both the economy and the financial system to various risks. In this case study, such as tool is prototyped and designed for a particular stakeholder, the European Central Bank (ECB), who is interested in the physical risk and the impacts that financial institutions have on climate change, biodiversity loss, ecosystem services and their degradation, but also on how these processes also have impacts on financial institutions.
Stakeholder needs:
- A tool to analyse the impact of various economic activities on ecosystem services degradation and vice-versa, and that allows them to understand the main components that are driving nature/climate and economic components
- That the methodology is designed to be transparent and interpretable
- That the tool is flexible and adaptable enough to work with sensitive data (i.e. the possibility to add data that is confidential)
Planned implementation:
This work is of very exploratory nature, as we first had to formulate the concept and explore its potential. This was done on an early ESDL data cube and with socio-economic data from the Global Data Lab, based on a 3-way Canonical Correlation Analysis (CCA) technique. The first tests have enabled us to construct a proof-of-concept, giving an idea of what could be expected, and developing a viewer to analyse the data. However, after some analysis and fruitful discussions with our stakeholder, we concluded the use case would benefit from an increase in spatial detail in all inputs. The current planned implementations thus relies on:
- Improving the viewer tool
- Consolidating the workflow in a deployable toolbox
- Revisiting the input data source
- Deliver the data, toolbox and viewer to the ECB so that they can explore and add their confidential data and provide feedback
Recorded talks (ordered chronologically):
- Integrated data-driven analysis of climate, biosphere and socio-economic co-variability by Wantong Li, Open-Earth-Monitor - Global Workshop 2023;
- Systemic human-biosphere-atmosphere monitoring and diagnostics by Gregory Duveiller, Open-Earth-Monitor - Global Workshop 2024;
Technical info
Visit the use-case page on the OEMC website to learn more: https://earthmonitor.org/planet-health-index/