Read this in The Manila Times digital edition.
WHEN a magnitude 7.5 earthquake struck northern Venezuela on June 24, rescue workers rushed toward collapsed buildings while scientists looked hundreds of kilometers above Earth.
Within hours, satellites were measuring ground deformation, mapping damaged communities and tracing the fault rupture that had torn across northern Venezuela. The data gave emergency responders one of the earliest broad assessments of the disaster while helping geologists reconstruct how the earthquake unfolded beneath the surface.
The same technology was deployed after the magnitude 7.8 earthquake that struck southern Mindanao on June 8. The Philippine Space Agency (PhilSA) analyzed data from multiple Earth observation satellites to identify damaged areas, detect landslides, monitor coastal uplift and even track the gradual return of electricity through nighttime satellite imagery.
The two earthquakes, occurring just weeks apart, illustrate how satellite technology has become an essential part of disaster response. Yet this capability is the product of more than five decades of scientific and technological progress.
Eye in the sky
Earthquake mapping began in 1972 with the launch of NASA's first Landsat satellite. Designed to photograph Earth's surface, Landsat transformed agriculture, forestry and environmental monitoring. After major earthquakes, scientists used its images to document landslides, fault scarps and changes to the landscape. The process, however, remained largely manual. Field teams still spent days or weeks surveying damaged communities before authorities had a clear picture of the disaster.
A major breakthrough came in the early 1990s with Interferometric Synthetic Aperture Radar, or InSAR. Unlike optical satellites that rely on reflected sunlight, radar satellites transmit microwave signals toward Earth and measure the returning echoes. By comparing radar images taken before and after an earthquake, scientists can detect ground movement with centimeter-scale precision across hundreds of kilometers.
Because radar penetrates clouds and operates day and night, it provides reliable observations even when storms or darkness prevent aircraft from flying. It has become one of the most valuable tools for studying earthquakes, volcanic eruptions and landslides.
Today, the challenge is no longer obtaining satellite images but interpreting the enormous volume of data they produce.
Modern Earth observation satellites generate thousands of images after every major disaster. Reviewing them manually can delay critical decisions during the first hours of an emergency, when rescue operations are most urgent. Artificial intelligence is helping bridge that gap.
AI analysis
Machine-learning algorithms rapidly compare satellite images taken before and after an earthquake, highlighting damaged buildings, blocked roads, landslides and shoreline changes that warrant closer inspection. Rather than replacing scientists, AI allows them to concentrate on verifying results and producing damage assessments far more quickly than traditional methods.
AI is also improving the usefulness of satellite imagery. Super-resolution algorithms sharpen lower-resolution images, while denoising techniques reduce atmospheric and sensor interference. These advances help analysts distinguish damaged structures, fault ruptures and subtle changes to the landscape that might otherwise be overlooked.
PhilSA's assessment of the Mindanao earthquake demonstrates how these technologies are being applied in here. Using radar imagery from the European Space Agency's Sentinel-1 satellites together with optical images from Sentinel-2, the agency mapped damaged structures, detected coastal uplift in Sarangani and identified possible landslides in Sarangani and Davao Occidental. It also analyzed nighttime images from the NOAA-20 satellite to identify communities affected by power outages and monitor the gradual restoration of essential services.
Researchers in Venezuela earthquake combined radar observations, optical imagery and pixel-tracking techniques to reconstruct the strike-slip rupture near Caracas. Their analysis detected more than three meters of horizontal ground displacement, helping refine early seismic models and providing a clearer understanding of how the fault moved during the earthquake. NASA's Nisar mission and the European Union's Copernicus Emergency Management Service also supplied data that supported damage assessments and humanitarian response.
Major fault line
For countries along the major global fault lines where earthquakes and volcanic eruptions happen side by side with destructive typhoons and other recurring hazards, satellite technology is becoming an increasingly important part of disaster preparedness. PhilSA has expanded its use of satellite data to support hazard assessment, emergency response and post-disaster recovery, while preparations continue for the launch of the Multispectral Unit for Land Assessment, or MULA, the country's largest Earth observation satellite.
As more satellites enter orbit, the amount of available data will continue to grow. Artificial intelligence is expected to play an increasingly important role in transforming those images into information that emergency managers can use within hours instead of days. Combined with AI, they are helping scientists understand earthquakes faster, direct emergency response more effectively and improve preparedness for the next major disaster.