From wildfires to gas leaks: How hyperspectral imaging detects disasters on Earth

By John Oncea, Editor

Hyperspectral satellites analyze Earth's chemical fingerprints from space, enabling crop protection, mineral discovery and environmental monitoring to combat pollution and climate change impacts.

A few summers ago we wrote about how infrared is being used to track wildfires. Well, hyperspectral imaging says, “Hold my beer.”

Hyperspectral imaging (HSI) is used not only to detect wildfire smoke from space, but also to detect pipeline leaks and other environmental problems, providing precise monitoring and exploration capabilities for companies and governments, and more.

HSI detects disasters on Earth by identifying the unique chemical signatures of objects based on the way they reflect, absorb or emit light of different wavelengths. HSI uses more bands of light than other spectral imaging technologies, dividing light into narrow spectral bands across the electromagnetic spectrum, typically between visible and infrared wavelengths.

HSI can be used to identify specific chemicals and materials in an image, which can be useful in a variety of applications. For example, HSI can be used to:

• Detect leaks in pipes
• Identify areas where wildfires may occur
• Discover valuable materials for mining
• Evaluate the health of plants
• Predict and monitor landslides
• Quantify weather events
• Detect largely invisible chemical threats

HSI can be used with space-based, airborne or unmanned aircraft systems, as well as laboratory-based imaging systems.

Disaster detection and analysis

HSI can detect and analyze different types of disasters by collecting detailed spectral information across hundreds of narrow wavelength bands, writes the World Economic Forum. This enables the identification of unique “spectral fingerprints” of materials and phenomena associated with disasters.

Take volcanic eruptions for example. HSI can detect precursor signals such as increased thermal activity and gas emissions before an eruption, writes NASA. In addition, it can track lava flows and ash clouds during eruptions, as well as monitor landscape changes and hazards post-eruption. The ability to detect subtle thermal and chemical changes allows early warning of volcanic activity.

HSI can also help monitor landslides by analyzing soil moisture content and composition to assess landslide risk, detect early signs of ground movement and instability, and map affected areas after landslide events. Combined with topographic data, detailed landslide susceptibility maps can be created.

During flood events, hyperspectral sensors can assess soil saturation levels to determine flood potential, map flooded areas and water depths, and monitor water quality and pollution in flood waters.

Oil spill? HSI excels at detecting and mapping oil spills by identifying the unique spectral signature of oil on water surfaces, estimating oil thickness and type, and monitoring the spread and environmental impacts of oil spills.

HSI offers several key benefits for disaster detection and response, including early warning, as the ability to detect subtle changes allows for earlier detection of potential hazards. It also enables detailed analysis as hundreds of spectral bands provide rich data for detailed assessment of disaster impacts and risks.

Satellite-based hyperspectral sensors can quickly survey large areas, with a single hyperspectral image providing comprehensive information about a disaster site, reducing the need for multiple data sources.

HIS, SAR, LiDAR and more

Although HSI is a powerful tool, it is important to note that it is often used in conjunction with other remote sensing technologies for comprehensive disaster monitoring and response, including multispectral imaging.

While hyperspectral sensors capture hundreds of narrow spectral bands, multispectral sensors capture fewer but broader bands. The combination enables hyperspectral data for detailed spectral analysis and multispectral data for broader coverage and higher temporal resolution. This integration enables both comprehensive monitoring and targeted analysis of disaster areas.

Synthetic Aperture Radar (SAR) provides high-resolution images regardless of weather conditions or time of day. Combined with hyperspectral data it enables:

• All-weather monitoring capabilities
• Detection of surface changes and deformations
• Improved identification of materials and objects

This integration is particularly useful for monitoring disasters such as floods or landslides under cloudy skies.

LiDAR provides detailed 3D topographic information. Integrating LiDAR with hyperspectral data enables:

• Accurate mapping of disaster impacts on the terrain
• Improved analysis of vegetation structure and health
• Better understanding of flood dynamics or landslide risks

Integration with ground-based data

For comprehensive disaster management, HSI data is often combined with ground-based information. This includes ground-based sensors that provide local data in real time. Integration with HSI enables calibration and validation of satellite-based observations as well as more accurate interpretation of spectral signatures. It also enables early warning systems for disasters such as floods or volcanic eruptions.

On-site assessments by disaster response teams can be combined with hyperspectral data to verify and refine remote sensing observations, assess damage to infrastructure and ecosystems, and guide resource allocation for disaster relief.

Finally, advanced data fusion techniques are used to integrate HSI with other data sources:

• Machine learning algorithms can combine multiple data types to improve disaster detection and classification
• Geographic information systems (GIS) integrate geospatial data from various sources for comprehensive analysis
• Time series analysis of combined data sets can reveal trends and patterns in disaster evolution

Applications in disaster management

This integrated approach improves various aspects of disaster management, starting with early warning. Combining hyperspectral data with other sources improves the detection of precursor signals for events such as landslides or volcanic eruptions.

Damage assessment is also improved as the integration of HSI with SAR and ground surveys provides a more comprehensive picture of disaster impacts. Response planning is improved as consolidated data sets help optimize resource allocation and guide rescue operations. Finally, long-term integration of hyperspectral and other data sources enables tracking of ecosystem recovery and reconstruction efforts, resulting in improved monitoring of recovery.

By leveraging the strengths of multiple remote sensing technologies and ground-based data, hyperspectral imaging contributes to a more comprehensive and effective approach to disaster monitoring and response.