Applying Earth Observation: Energy Poverty

Berlin at Night

The 3,5-year project EnergyMeasures is wrapping up in Brussels. The EU-funded project was launched to identify households affected by energy poverty, to develop strategies that would  support them in adopting less energy-intensive behaviours, and to provide decision-makers of all levels with evidence-based policy recommendations to tackle energy poverty. As the project winds down, one of the key conclusions was to acknowledge the structural nature of energy poverty, necessitating European-wide comparison, based on coherent data. Writing from the perspective of the Domino-E project, it is the aim of this newspost, to outline some approaches of how EO data could become a valuable complement to projects like EnergyMeasures already in the near future. 

Identifying households with limited access to electricity 

In EnergyMeasures, a large part of the recruitment of affected households worked through public calls, and available data from already established energy consulting and EnergyPoverty Hubs. The approach was targeted and possible only because of the strong roots of the partners in the regions. It is unlikely that this could be easily replaced – after all, face-to-face contact with those affected remains the gold standard in attempting to change behaviour.

However, where EO data could have made a contribution is in comparing the availability and vulnerability of the infrastructure, which can reflect inequalities at a meta-level. EO data can be used to map the distribution of electricity infrastructure, such as power lines and distribution stations, as well as the presence of renewable electricity sources in the region or for individual households. For energy infrastructure in particular, the relevant indicators have already been identified today – at least this is what Yongze Son and Peng Wu argue for in their review of the state of Earth Observation for Sustainable Development.  

Picture 1Geothermal Power Stations, Kenya satellite image from Pléiades Neo; Copyright: Airbus DS 2022. 

Monitoring energy consumption and evaluating solutions to localised energy poverty 

As it is not possible to track energy consumption patterns at the household level using EO, it can be used to monitor energy use in different sectors, such as households, industry, and transport. The best known method of monitoring electricity using EO data measures the consumption of electricity and other forms of energy by tracking changes in night-time lighting (NTL) over time. So far, this method has proved particularly useful in developing countries, where access to household energy consumption data is often limited. But even in EnergyMeasures, did researchers found that access to energy consumption data can be limited by privacy concerns. EO data can provide standardised data over time, even at street level, without compromising individual privacy.

Picture 2Berlin at Night (While in the western part of the city, the network of gas street lighting in residential and streets was repaired and technically upgraded, the eastern part of the city was essentially converted to electric power). Copyright: ESA, 2022. 

A faster and more comprehensive assessment of which method of local power and energy generation is the next step and is likely to be available soon at household level. Mariarosa Argentiero and Paquale Marcello Falcone state that the Sentinel constellation could be used to implement partially automated analyses for sustainable energy projects on small scale level. EO data would allow public authorities to significantly reduce the time and cost of feasibility studies, and specialist companies to install power plants more quickly. Increasing the total amount of energy available could help bring down the cost of energy. 

Democratizing Earth Observation for Energy Poverty Solutions: A Paradigm Shift from Product to Service.

While there are many examples of how EO data can be used to assess energy poverty at a variety of scales, from local to global, what remains unresolved is the frequent availability of data at low cost. To make EO a versatile tool that can be used to inform policy decisions at all levels of government, we need an approach that sees EO as a service rather than a product. Only if EO providers can reduce their costs will EO become a basic tool for researchers and policy makers in the field of energy poverty and beyond. If it does, it could inform new studies, provide the basis for site selection, and provide essential support for monitoring the success of interventions. It could finally kick-off a new complement to the EnergyMeasures project – a monitoring and assessment mission based on EO data.