1.5. Summary
- Hyperspectral Imaging (HSI) captures hundreds of narrow, contiguous spectral bands across visible, near-infrared, shortwave infrared, and sometimes thermal regions, providing detailed spectral signatures for every pixel.
- HSI is based on the physics of electromagnetic reflectance, allowing identification of materials by how they absorb and reflect light.
- Key sensor characteristics include spectral bands, spectral resolution, and Full Width Half Maximum (FWHM), which determine the sensor’s ability to detect subtle material differences.
- Hyperspectral sensors are deployed on various platforms:
- Spaceborne satellites (e.g., Pixxel’s Firefly constellation) for large-scale monitoring
- Airborne systems for regional, high-resolution data
- UAV and handheld devices for local-scale, flexible studies
- HSI enables precise material identification and classification, revealing details not visible to traditional or multispectral imaging.
- Common applications include agriculture, mineral exploration, water quality monitoring, environmental assessments, urban planning, and defence.
- Due to the high volume and dimensionality of hyperspectral data, specialised preprocessing and analysis methods are essential to extract meaningful insights.
- Mastering these fundamentals provides a solid foundation for understanding the broad range of HSI applications explored in the following chapters.
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