Enhancing Disaster Preparedness Through Remote Sensing Strategies

Imagine a world where the relentless force of nature unleashes its fury, where cities crumble and landscapes transform instantly. What if, in the blink of an eye, our very existence is rewritten by the power of natural disasters?

Although the impact of natural disasters varies significantly by region, approximately 45,000 people globally die from natural disasters each year. Are there more natural disasters now than there were 5 years ago? Yes. Worldwide, in 2017, 335 natural disasters killed 9,697 people, and in 2022, 387 natural disasters (higher than the past three decades' annual average of 340) killed 30,704 people. And there is no sign of those numbers decreasing anytime in the near future, with the world expecting 560 annual natural disasters by 2030.

Why are the number of natural disasters increasing?

Natural disasters are not entirely preventable because they are primarily controlled by natural processes and beyond human control. These events include geological processes like tectonic plate movements (earthquakes and volcanoes), meteorological processes (hurricanes, tornadoes, and floods), and climatological processes (droughts and heatwaves). While human activities can increase the impacts of some natural disasters, they do not create the underlying natural disasters themselves. Here are some human-related factors that are resulting in the increase in natural disasters:

1. Climate change: Rising global temperatures lead to more frequent and severe weather events, such as hurricanes, floods, droughts, and heatwaves. Climate change also contributes to the melting of glaciers and the rise in sea levels, increasing the risk of coastal flooding and storm surges.
2. Deforestation: Removing forests can lead to increased runoff and soil erosion, which can result in more frequent and severe landslides and floods.
3. Urbanization/Poor Infrastructure: The rapid growth of cities and urban areas often leads to poor land-use planning and the construction of infrastructure in disaster-prone zones. Inadequate infrastructure and building standards in some regions make people more vulnerable to events like earthquakes, hurricanes, and flooding.

Even though natural disasters have the potential to decrease in numbers with the decrease of these human activities, natural disasters will occur no matter what.

Although natural disasters are not preventable, the high rate of human deaths is. But, how?

Remote Sensing! It detects and monitors the physical characteristics of Earth’s surface and atmosphere from a unique vantage point using aerial platforms such as satellites, for purposes ranging from scientific research to disaster management.

Remote sensing provides detailed information about the affected area, which helps to identify the location, severity of damage, and further possible risks/effects to residents and infrastructure. For example, thermal imaging technology identifies wildfire locations and guides firefighters to disperse according to the danger zones. Essentially, the collected data improves the accuracy of the emergency response and evacuation plans.

Alright, let’s get into the nitty gritty of satellites!

Here’s the process of how the satellites take part in capturing data and images from space during disaster control:

1. Satellites have these sensors that contribute to capturing data and images:

• Solar arrays on satellites convert solar energy into electrical power to operate the satellite’s instruments, sensors, and communication systems.
• Solar ultraviolet imagers are instruments used to observe the sun in the ultraviolet part of the spectrum. They can provide valuable data regarding solar activity and its potential impacts on Earth’s climate and space weather, which can influence natural disasters.
• Extreme ultraviolet and X-ray irradiance sensors measure solar radiation in the extreme ultraviolet and X-ray wavelengths. They monitor solar flares and solar eruptions, which can cause geomagnetic storms (harmful to power grids and pipelines) and impact communications.
• The Geostationary Lightning Mapper sensor is specifically designed to monitor lightning activity from a geostationary orbit. It can provide valuable data for tracking and interpreting thunderstorms, often associated with severe weather events like tornadoes and flash floods.
• Magnetometers measure the strength and direction of magnetic fields in space. They are used for studying the Earth’s magnetic field, but they also play a role in understanding space weather and how it impacts technological systems and infrastructure.

Remote Sensing Satellite

2. Satellites can orbit the Earth at different altitudes and orbits, such as polar and geostationary orbits:

Comparing Polar vs. Geostationary

Geostationary satellites are valuable for real-time monitoring of rapidly changing events and providing continuous updates, making them essential for early warning systems and immediate response to events like hurricanes or flash floods. Polar-orbiting satellites offer global coverage and high-resolution data, which is valuable for disaster assessment, research, and monitoring of long-term environmental changes.

Polar vs Geostationary Orbit

3. The data is transmitted back to Earth via radio waves and received by space agencies such as NASA.

4. The raw sensor data is converted into usable information and complex algorithms are used to calibrate data to extract the key takeaways. The data is distributed to government agencies, disaster management authorities, researchers, and the public to collaborate on the best plan of action to ensure public safety.

5. It’s possible that the data could trigger emergency alerts. (Yes, those flash flood warnings that we get originate from satellite data!)

6. During the aftermath of the disaster, the satellite continues to monitor the area to assess the damage by comparing pre-disaster and post-disaster images. This pinpoints the specific areas that need prioritized assistance.

Remote Sensing IRL

In 2010, Haiti faced a devastating earthquake with a magnitude of 7.0 which caused extensive destruction to the capital of Port-au-Prince and led to the death of 316,000 people. Haiti did not have any type of early warning system, such as remote sensing technology, even though the country sits on a fault line between huge tectonic plates, indicating that it is prone to earthquakes. Having a preparedness system could have potentially reduced the extent of damage caused by the earthquake. However, remote sensing was used for disaster response and recovery efforts. Remote sensing used thermal imaging from aircraft and drones to identify the heat signatures of survivors trapped in the rubble. Remote sensing tech was also used to create infrastructure mapping which showed damaged infrastructure, blocked roads, and areas at high risk of landslides or further collapse. Post-disaster, the data collected by the Phased Array-type L-band SAR (PALSAR) instrument onboard the Advanced Land Observing Satellite (ALOS) aided in identifying locations to set up distribution centers and manage temporary housing settlements. Essentially, remote sensing helped save thousands of lives, optimize resource allocation, and guide recovery efforts; but hundreds of thousands could have been saved with the use of an early warning system.

Haiti post-disaster (2010)

Now let’s take a look at another case study:

The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) Geostationary Operational Environmental Satellite (GOES) series in 2016. The GOES-16 and GOES-17 (two satellites from the GOES series) were used for weather monitoring, climate research, disaster management, environment monitoring, and space weather. One of the impressive features that GOES-16 has is that it can scan the Western Hemisphere every 15 minutes, the Continental U.S. every five minutes, and areas of severe weather every 30–60 seconds, all at the same time!

In 2019, the Bahamas and the southeastern part of the U.S. were affected by Hurricane Dorian, a category 5 hurricane (the most severe category, with wind speeds of 157 miles per hour or higher). As the hurricane was approaching, GOES-16 and GOES-17 provided real-time monitoring of the storm’s development. These satellites offered continuous updates on the hurricane’s size, structure, and movement, allowing authorities to make informed decisions and coordinate response efforts. Remote sensing data and technology identified high-risk areas, allowed for the prediction of the hurricane’s path and landfall location, enabling authorities to issue timely warnings and evacuation orders, and helped meteorologists predict the hurricane’s intensity and potential impacts, aiding in disaster preparedness and response planning. The hurricane swept away with the loss of approximately 74 people and an additional 282 people missing at the time.

Hurricane Dorian Path and Pattern

Although we can not compare the results of Haiti’s 7.0 magnitude earthquake to category 5 Hurricane Dorian due to their differing economic conditions and time (year) of occurrence, it is reasonable to wonder how either situation would have resulted in the case that Haiti had an early warning system, and the Bahamas and the U.S. did not have a system.

Remote Sensing Is Not Always Effective…But It Can Be

Cloud cover can turn out to be a significant challenge since the region’s cloudiness obstructs satellite views. Satellite-based remote sensing relies on capturing clear, high-resolution imagery of the Earth’s surface to monitor and respond to evolving disaster situations. However, cloud cover can obscure vital information and disrupt real-time monitoring. This limited the ability to assess flooding patterns, determine the extent of the disaster, and plan evacuation and relief efforts effectively.

One solution to address the cloud cover issue is the utilization of radar sensors on satellites. Radar sensors, such as those on the European Space Agency’s Sentinel-1 satellites, can penetrate cloud cover and provide detailed information about ground conditions. During the 2019 Cyclone Idai in Mozambique, the radar capabilities of Sentinel-1 were instrumental in mapping flooded areas, even in the presence of heavy cloud cover. This technology enabled emergency responders to better understand the disaster’s impact, assess the extent of flooding, and locate affected populations.

Moreover, frequent satellite revisits and enhanced data processing techniques offer opportunities for mitigation. For example, in monitoring the wildfires in California over the past decade, polar-orbiting satellites, such as NASA’s Aqua and Terra, made multiple daily passes to capture imagery when cloud cover cleared. By combining data from multiple visits and using cloud-detection algorithms, analysts could generate composite images that provided a comprehendible view of the disaster. These techniques have the potential to reduce the impact of cloud cover on remote sensing for natural disaster preparedness, improving our ability to respond effectively to crises.

NASA’s

The Future of Remote Sensing in Disaster Control

With the continuity of advancements in technology and applications, remote sensing for disaster control holds great promise. With the incorporation of AI and ML, there is a possibility of automating the analysis of remote sensing data. This would speed up the data processing, and synchronize anomaly detection with extracting observations.

Pacific Northwest National Laboratory (PNNL) researchers are using AI techniques to predict and plan for emergencies, such as wildfires and hurricanes, as well as to help respond and recover from them as quickly as possible. They developed a software tool called RADR (Rapid Analytics for Disaster Response) to provide awareness regarding natural disasters and damage assessments within hours of a natural disaster or other emergency. RADR uses image-capturing technology, AI, and cloud computing (delivering computing services over the Internet) to predict events and assess damage.

The advancements in space technology are paving the way for a bright and promising future for remote sensing in natural disaster preparedness, offering the potential to enhance our ability to monitor, respond to, and minimize the impact of disasters on a global scale!

Do you believe that remote sensing is the best form of preparedness or another system that could be more beneficial in these technologically advancing times?

Key Takeaways

1. The frequency of natural disasters is increasing globally, with a rise in the number of annual disasters and casualties over the past decade, indicating the urgent need for disaster preparedness.
2. While human activities can exacerbate the impacts of natural disasters, the underlying causes are primarily geological, meteorological, and climatological processes beyond human control.
3. Remote sensing technology, through satellites and advanced sensors, provides crucial data for disaster preparedness and response, aiding in early warning, damage assessment, and evacuation planning.
4. Cloud cover can obstruct satellite views, but solutions such as radar sensors and advanced data processing techniques offer ways to mitigate its impact on remote sensing.
5. Advancements in space technology and the integration of AI and ML hold great promise for the future of remote sensing in disaster control, improving response times and disaster prediction accuracy.