> For the complete documentation index, see [llms.txt](https://guides.geospatial.bas.ac.uk/spectral-analysis-of-imagery/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://guides.geospatial.bas.ac.uk/spectral-analysis-of-imagery/spectral-profiles-and-reflectance-curves.md).

# Spectral profiles and reflectance curves

Objects on the ground will absorb and reflect different levels of energy from the sun across the electro-magnetic spectrum. 

The graph below illustrates the spectral response curves of some common types of objects and ground conditions, and the degree to which the objects reflect energy depending on wavelength. 

Knowing these spectral responses is a starting point for understanding how to process the spectral information collected within the imagery bands. 

![Credit: National Ecological Observatory Network (NEON)](https://2016800125-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FpQSDh3IPyvK1x3GCRlei%2Fuploads%2FZgKgLmx9ii28Z2RGl6TG%2Frelfectance-curve.png?alt=media\&token=a3f8bb98-1aa5-47d0-be67-428f5900bd72)

{% hint style="info" %}
These spectral response profiles are based on the  reflectance of the materials under perfect laboratory conditions. In real-world remote sensed imagery, we would likely see slight variations on this, with potentially less of a string signal, due to other factors coming in to play.
{% endhint %}

When we take the reflectance of these materials measured by the spaceborne Sentinel-2 sensor within each discreet band, and plot these against reflectance, it is clear that there is a lot of the shape of the idealised response curve missing from the data we have available for processing. 

![Credit: Kamusoko et al 2021 Exploratory Analysis and Transformation for Remotely Sensed Imagery](https://2016800125-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FpQSDh3IPyvK1x3GCRlei%2Fuploads%2FvzZTFvPUaBch1YjOYmez%2Freflectance-curve-2.png?alt=media\&token=89d3d868-98e9-4c31-9661-1e928652d54e)