1.2. The Physics Behind Hyperspectral Imaging

Every pixel in a hyperspectral image contains rich spectral detail, but to truly understand what makes hyperspectral data so powerful, it's essential to grasp a few key concepts in spectrometry.

Hyperspectral imaging is based on the physics of electromagnetic reflectance, i.e., the way materials absorb and reflect specific wavelengths of light. When sunlight interacts with the Earth’s surface, each object reflects a unique pattern of light across the electromagnetic spectrum.

The Electromagnetic Spectrum, Bands, and Spectral Resolution

Hyperspectral sensors collect data across a continuous portion of the electromagnetic spectrum (EMS), typically spanning the Visible and Near Infrared (VNIR), Shortwave Infrared, and in some cases, the Thermal Infrared (TIR).

Each pixel in a hyperspectral image contains a reflectance spectrum: a detailed curve showing how that material interacts with light across the EMS, which can be analysed to determine material composition. To understand the richness of this information, it’s important to know how bands, spectral resolution, and bandwidth shape the data.

Feature	Description
Spectral Band	A specific range of wavelengths captured by an imaging spectrometer. For example, wavelengths between 695 nm and 700 nm may form a single band. Spectrometers collect reflected light within that range and record it as a single value per pixel. Band information is often reported using the centre wavelength, the midpoint of the wavelength range (e.g., a 695–700 nm band has a centre wavelength of 697.5 nm).
Spectral Resolution	The narrowness of each band captured by a sensor. For example, if a sensor collects light from 695 nm to 700 nm in a single band, its spectral resolution is 5 nm. Higher spectral resolution, i.e., narrower bands, enables the detection of subtle material differences that broadband sensors might miss.
Full Width Half Maximum (FWHM)	Measures the effective width of a band around its centre wavelength—specifically, the width of the band at half its maximum response. While spectral resolution gives the total range, FWHM shows the sharpness of the band response and may vary between bands on the same sensor.

Together, spectral band positioning, resolution, and FWHM determine how well a hyperspectral sensor can detect fine variations in reflectance, essential for analysing the Earth’s surface.

Not all hyperspectral sensors are designed with equally spaced or uniformly wide bands. Some systems, such as Pixxel’s Firefly constellation, are optimised with variable bandwidths to enhance detection of specific features in different parts of the spectrum.

Predefined band combinations for Pixxel's Firefly constellation.

HSI is also called an imaging spectrometry technique, merging two capabilities: the spatial resolution of imaging and the compositional insight of spectroscopy. This dual nature means hyperspectral data answers both "Where is something?" and "What is it made of?"

VNIR, SWIR, and TIR regions

Hyperspectral sensors often span one or more of the following spectral regions, each revealing unique information:

Spectral Region	Wavelength Range (nm)	Key Applications	Key Absorption Features
VNIR	400–1000	Vegetation health, water bodies	Chlorophyll, carotenoids, water
SWIR	1000–2500	Mineral mapping, soil moisture, agriculture	OH, CO₃²⁻, SO₄²⁻, clay minerals
TIR	8000–14000	Thermal mapping, industrial monitoring	Emissivity, surface temperature

Each of these regions reveals different physical and chemical properties of Earth's surface materials. For example, while VNIR is responsive to surface reflectance from vegetation and water, SWIR provides deeper compositional insight—such as whether a crop is water-stressed or if a rock contains clay minerals. TIR, though less common in hyperspectral imaging due to detector limitations, is valuable for studying temperature gradients and emissivity differences.

Advanced hyperspectral sensors can capture combinations of these regions in a single system, enabling multi-domain insights from vegetation health to thermal anomalies.

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