As our global climate continues to undergo profound transformations, the challenges posed by climate change are increasingly felt across various sectors of society, including critical infrastructure.

Climate change, characterized by rising temperatures, increased occurrences of extreme weather events, and shifting precipitation patterns, have exposed vulnerabilities within power networks. Often designed under the assumptions of historical climate patterns, now they are increasingly susceptible to the new normal of extreme weather, prolonged heat waves, and more severe freezing.

National Grid Energy Transmissions (NGET), which owns and maintains the high-voltage electricity transmission network in England and Wales, conducts invasive analysis annually to monitor the towers most at risk of movement. Moreover, the NGET inspection teams perform annual line walking activities and monthly substation inspections during which they visually assess the presence of asset motion. These interventions are crucial to avoid issues which may cause expensive assets replacements or reconstruction. It costs NGET over £6 million per year to monitor only 1% of their most at risk assets.

The operation of oil and gas transmission pipelines entails inherent risks associated with the potential for unintentional product releases. Oil and gas product releases have traditionally been treated as safety issues due to the risk of explosions and asphyxiation, but increasingly, the environmental impact of unintentional product releases is fast becoming the key risk to be reduced and avoided via Leak Detection and Repair (LDAR) programs.

Spottitt is known for utilising satellite data to offer infrastructure owners valuable insights into the diverse external risks affecting their assets. But how precisely do we derive these insights from satellite imagery? The answer is – machine learning, and today we’re inviting you behind the curtains of our product to unveil the whole process.

In this piece, we delve into the realm of satellite technology, focusing on the determination of vegetation height and the planning of routes for electrical distribution lines.
Additionally, we examine the algorithm that empowers open-source meters in resolution SAR sensors to measure millimeters per year of land or asset motion. We also provide an overview of the driving forces behind the application of satellite technology for monitoring methane and other greenhouse gases.