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**Hyperspectral remote sensing** collects data in **hundreds of narrow, contiguous spectral bands** (typically 5–10 nm wide) rather than a handful of broad ones. This produces a full reflectance spectrum for every pixel, which can be matched against lab spectra to identify specific minerals, vegetation species, and pollutants. - **Example sensor:** Hyperion on **EO-1** — 220 bands, 0.4–2.5 µm, 30 m pixels, 705 km orbit. - **Trade-off:** massive data volume and low SNR per band; redundancy usually reduced via PCA or minimum-noise-fraction (MNF) before classification.

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