Applying Earth Observation: Energy Poverty

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…

Published

Along the river: the stream of Earth observation

Rivers are divided into upstream, midstream, and downstream. This tripartite division also helps to understand the earth observation processing chain. Rivers are traditionally divided into three sections along their course based on the gradient between their source and delta: upstream, midstream and downstream. This division is often used metaphorically to describe industrial value chains.  The…

Published

Machine learning in Domino-E use cases

What exactly is machine learning (ML) and  how does Domino-E make use of it in planning, resource allocation and human-computer interactions? In what ways does it benefit users? In this article we focus on answering these and other questions regarding machine learning in Earth Observation.  Earth Observation (EO) produces a vast quantity of often unstructured data.…

Published

Climate change tracking from space: From mono to multi-mission design 

Photo by ROMAN ODINTSOV: https://www.pexels.com/photo/aerial-shot-of-heaps-of-icy-snow-on-a-glacier-and-turquoise-melted-ice-6979890/

Earth observation satellites provide valuable information on greenhouse gas emissions, deforestation, melting glaciers, and other indicators of climate change. The move from mono- to multi-mission design allows better data access.

Published