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Moving on in the world of remote sensing domains, we will introduce another important variable, which is used to characterize a sensor. The spectral resolution can be seen as the ability of the sensors eye – the instrument measuring capabilities. Let’s start with a short video giving you an overview of spectral resolution and sensors that cover this domain in different ways.

What is spectral resolution

The spectral resolution of a given remote sensing sensor describes the ability to monitor the Earth’s surface at specific wavelengths. A sensor with a finer spectral resolution provides more narrow spectral bands (less wavelength covered per individual band). The range of spectral resolution varies between panchromatic (a single and quite wide band) and hyperspectral (100s to 1,000 very narrow bands) sensors. In between these, multispectral instruments can be found. Take a look at the image below to understand how the number of bands influences and signatures that are created the way, a given area is monitored.

Increasing spectral resolution from multispectral (left) to hyperspectral (right) dimensions. Source: Edmund Optics

With higher spectral resolution, a sensor can store more bands, containing grey values representing a greater number of wavelength parts.

Influencing factors of spectral suitability

In order to determine which spectral bands are appropriate for certain land applications and consequently for a sensor two important factors should be considered: 1) atmospheric windows and 2) the spectral signature of objectives that are ought to be observed.

Atmospheric windows

What spectral sensors (shorter wavelengths) see, depends on the atmosphere and its structure, or, whether the wavelengths can surpass the atmosphere or not. Wherever gases or small particles like water drops or dust molecules dominate the atmospheric layer, more parts of the EM spectrum will be absorbed or scattered, resulting in less strong reflectance towards the remote sensing instrument. However, there are some portions of wavelength that are able to travel through the atmosphere more easily, these parts are called atmospheric windows. Consequently, the atmospheric opacity determines which wavelength can travel without loosing too much intensity.

The typically used sensor wavelengths feature a low atmospheric opacity, allowing use to analyze them. Source: CIMSS 2017

Spectral signatures

The so-called ‘fingerprint’ of specific land cover/use objects, is an important tool to monitor changes over time. In the figure below you can easily distinct between the view a hyperspectral sensor (in this case DESIS from DLR) has on grasses and water surfaces.

The graph above displays several spetral signatures of different land cover types in the area of Jena, Germany. DESIS (spectral range from 400 nm to 1,000 nm) hyperspectral data served as input.

Since the rates of bottom of atmosphere (BOA) reflectance varies significantly between different land cover/use types, very unique signatures can be found. These can be used to distinguish finest sub-classes of land cover/use types. Understanding of the spectral fingerprint of objects is important, to be able to evaluate changes observed from remotely sensed data.