Methodology · Imaging spectroscopy

Hyperspectral classification

Identifies surface materials or land-cover classes from full spectral fingerprints; good for geology, vegetation stress, and mineralogy mapping.

How it works

Matches per-pixel spectra against reference libraries or trained classifiers. Accuracy depends heavily on cross-sensor calibration consistency. [Wikipedia: Hyperspectral imaging](https://en.wikipedia.org/wiki/Hyperspectral_imaging)

Topics this serves

Existing implementations

Demonstrated

Capable, undemonstrated

None on record.

Related methodologies

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Detects gas absorption features (CH4, CO2, CO) at SWIR wavelengths from a single point or facility source; good for industrial emissions monitoring and leak detection.
SWIR absorption - regional flux

Estimates area-integrated greenhouse gas flux over agricultural, wetland, or basin-scale regions; good for national inventory support and carbon accounting.
SWIR absorption - global screening

Wide-area survey for anomalous methane or CO2 concentrations at coarse spatial resolution; good for prioritising follow-up with finer sensors.

Sources

[wikipedia]Wikipedia: Hyperspectral imagingcommunityaccessed 2026-05-22

Methodology

Edited from public sources. Last reviewed date pending by SpectraWorks editorial. See the data dictionary for field definitions.

Cite or share

https://eo-atlas.org/topics/methodologies/hyperspectral-classification

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