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The most significant characteristic of hyperspectral remote sensing data is its integration of traditional image-dimensional and spectral-dimensional information. While acquiring images of the Earth's surface, it also obtains continuous spectral information for each land feature, enabling the retrieval and identification of land feature composition based on their spectral characteristics. As the spectral resolution of hyperspectral imaging improves, its detection capabilities also increase.

Compared with panchromatic and multispectral imaging, hyperspectral imaging has the following significant advantages: (1) it has nearly continuous spectral information of land features; (2) it greatly improves the ability to detect and identify land cover; (3) there are a variety of methods for classifying and identifying topographic features; and (4) quantitative and semi-quantitative classification and identification of topographic features will become possible.