Landsat's Role in Responding to Disasters
In 2022, the Emergency Events Database (EM-DAT) reported 387 natural hazards and disasters worldwide, resulting in the loss of over 30,000 lives and affecting more than 185 million individuals. Economic losses totaled around US$223.8 billion. Fires, floods, heat waves, drought, hurricanes, tornadoes, and other natural disasters can be particularly tragic and costly when critical facilities such as power plants, airports, roads, and hospitals are threatened. When a disaster strikes, remote sensing is often the only way to get a big-picture view of what is happening on the ground. With its consistent, reliable, repeated observations of Earth’s changing surface, Landsat keeps a record of Earth’s land surfaces before and after disasters, serving as an essential tool for assessing risk, mapping the extent of damage, and planning post-disaster recovery. Landsat produces 185-kilometer-wide images with 30-meter resolution in visible and infrared wavelengths of light, making it possible to map impacts on the landscape in ways otherwise not visible to human sight. For example, Landsat sensors enable us to see the heat from fires both during and after the burns, and the lava flows from volcanic eruptions even when gaseous substances obscure the view to human eyes.
When Landsat’s vast decades-long archive is combined with data from other instruments it can provide amazing insight into how our world is evolving with us and around us. Here are some of the ways Landsat and GEDI data are being harnessed to help us better understand the complex relationship between humanity and nature.
Over the past few years, machine learning techniques have been increasingly used to analyze the vast amount of data collected by the Landsat mission, which has been circling the globe for over 50 years.
Merging data from multiple satellites, OPERA can help government agencies, disaster responders, and the public access data about natural and human impacts to the land.
UCONN remote sensing experts used Harmonized Landsat Sentinel-2 imagery to quickly assess damage caused by the storm’s aftermath, providing spatially-relevant situational awareness that could aid rescue efforts.