Remote observation technologies are basic tools used to collect accurate information in real time. The combination of different technological elements facilitates the efficient coordination of rescues and the provision of assistance, as well as making it possible to understand the magnitude and impact of natural catastrophes. Damage assessment following a natural disaster is one of the most critical tasks in the management of emergencies. This process, which is key to organizing relief, humanitarian aid and reconstruction efforts, relies on equipment that is capable of rapidly collating information visually. In this context, satellites and drones are gaining prominence as the most effective solutions, in that they provide a complete and precise perspective of the affected areas. In recent years, these technologies have evolved, offering complementary capabilities that improve the quality of the data obtained and accelerate decision-making.
Satellites: a global perspective
Located in Earth’s orbit, satellites provide a broad and continuous view of the impacted surfaces, enabling large-scale events such as hurricanes, earthquakes, floods or forest fires to be monitored. Equipped with advanced sensors, they capture images from large areas, enabling rapid analysis even in remote or inaccessible areas.
Programs such as the European Union’s Copernicus, have shown how satellites can supply open and accessible data to respond to natural disasters. For example, during the floods in Libya in 2023, the Sentinel system, equipped with synthetic aperture radars (SAR), delimited flooded areas, detected isolated communities and assessed infrastructure damage, even under adverse weather conditions. SARs can generate high-resolution images that penetrate clouds, smoke and vegetation, facilitating the analysis of structural impacts and topographic alterations.
In addition, satellites capture multispectral and hyperspectral images that make it possible to identify impacts not visible to the human eye, such as water stress in crops, chemical alterations in water bodies and the degradation of construction materials. The ability to program periodic observation ensures the continuous supervision of dynamic phenomena, optimizing emergency management and response planning.
One of the most recent innovations is the use of radar satellites to measure movements in the Earth’s crust after an earthquake. This was essential in the earthquakes in Turkey and Syria in 2023, where interferometric SAR images allowed tectonic movements to be accurately mapped, thereby helping to assess additional risks.
Drones: agility and precision in the field
While satellites offer global coverage, drones complement their scope by providing a detailed vision at ground level. Their ability to fly at low altitudes allows them to access specific areas with millimetric precision. Equipped with multi-spectral sensors, high-resolution and thermal cameras, drones are versatile tools that can be deployed to examine infrastructure and monitor affected areas in real time.
In emergency situations, drones use technologies like Ground-Penetrating Radar (GPR), which is capable of detecting people trapped under debris or identifying cavities after structural collapses. In the aftermath of the earthquakes in Turkey and Syria, drones played a crucial role in determining damages in urban areas, identifying critical areas for rescues and mapping supply delivery routes.
Beyond rescue missions, drones are also used in long-term risk management. In Japan, for example, they have been used to monitor active volcanoes, capturing images and data that help predict eruptions and reduce the impact on nearby communities. They are also useful for assessing coastal erosion after a tsunami, providing key information that can guide the construction of protection barriers.
Integration of advanced technologies
The integration of artificial intelligence (AI) and machine learning in damage assessment has transformed the way in which the data obtained by drones and satellites are processed. Image segmentation algorithms can automatically identify affected areas, differentiating between urban areas, vegetation and water bodies. Predictive AI also models the evolution of disasters, such as the spread of forest fires or the trajectory of hurricanes, optimizing evacuation efforts.
During the fires in Australia in 2019, deep learning models quickly classified the damaged areas, helping to prioritize relief resources. This approach not only managed to locate losses, but also anticipate areas at risk and mitigate future threats.
Combining AI with drones and satellites has also opened up new possibilities for post-disaster reconstruction. For example, in Haiti, after the 2021 earthquake, machine learning algorithms were used to analyze aerial images and prioritize the reconstruction of key infrastructure elements, such as hospitals and roads. This significantly accelerated the planning and execution processes.
The future of disaster assessment
Damage assessment continues to improve as remote sensing technologies and the satellite capacity gets better. Next generation satellites, like the WorldView Legion system and Capella Space’s radar satellites, optimize image resolution and frequency, which facilitates accurate inspection of affected areas in real time, even under extreme conditions.
Although constellation systems like OneWeb and Starlink are not specifically designed for remote observation, their satellites are contributing to enhanced global connectivity, a crucial factor in regions where meteorological events have destroyed land-based infrastructure. These systems allow for fast data transmission and remote access to critical information in real time, effectively complementing response and coordination efforts in emergency situations.
In addition, the integration of autonomous drones and IoT sensors look set to collect even more efficient data in the future, enabling continuous tracking of the affected areas and improved response capacity.
The synergy between satellites, drones and advanced technologies such as AI will lay the groundwork for creating more agile and intelligent response systems capable of predicting phenomena such as earthquakes, floods and forest fires, and providing communities the information necessary to prepare and mitigate the effects of these catastrophes.
