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Infrared Plants

Different surfaces reflect electromagnetic waves (like the visible range of the sunlight) in varying intensities. Black surfaces reflect less sunlight than white surfaces. But there's even more to it. Characteristically, surfaces reflect some parts of the electromagnetic spectrum stronger than other parts. Green vegetation, for instance, absorbs blue and red light strongly, but reflects green and infrared light even more.

Those characteristic reflection and absorption values distinguish objects from each other. Similar to individual human fingerprints, objects have their own spectral features - therefore, we call it a spectral fingerprint.
Looking at the animation below, we can see how the spectral fingerprint of dry ground, water and different vegetation states varies. The animation shows the differences between the reflection behaviour of the surfaces in the blue, green, red and infrared range of light.

 


Clicking on the buttons on the bottom of the image, the spectral fingerprint of water, soil, and different states of vegetation can be seen. 

 

Vital and green vegetation has a characteristic spectral fingerprint. This is due to the leaves and their special characteristics: They contain colour pigments like chlorophyll absorbing the blue and red range of light and reflecting the green range. The leaves appear green-coloured. The reflection in the infrared range, which is invisible for humans, is even stronger. This is caused by multiple reflection of the infrared light within the leaf cells. Because of the high values in infrared reflection, vital plants (much chlorophyll and solid cell walls) are prominent in the infrared band of satellite images.

 

Reflection, absorption and transmission: See their effect by clicking on the buttons.

 

The different layers of a leaf each have an influence on the incident ray of light. The animation shows reflection, absorption and transmission of light. According to where and how wavelengths are influenced, the spectral fingerprint of vegetation is formed as can be seen in the animation below:



The spectral fingerprint of a leaf in the course of time.


 

This animation shows you how the reflection characteristics and thus the spectral fingerprint of a leaf change in the course of time. You can clearly see that the difference between reflected light in the visible range and reflected light in the invisible range of healthy plants is quite striking. If a plant withers, this difference diminishes rapidly. In remote sensing, this phenomenon led to the development of a measurement indicating the vitality (= health) of vegetation. This measurement is called NDVI, which is short for Normalised Difference Vegetation Index.

 

NDVI-Bild des Mittelmeerraums


NDVI-image of the Mediterranean area. Almost unvegetated areas are clearly visible (processed image of USGS/NASA Landsat Program).

 

The NDVI is the quotient of the difference and the sum of the red and the infrared band. Thus, absorption characteristics (red band) and reflection characteristics (infrared band minus NIR) are being offset against each other. To put it simply: The higher the NDVI value of a pixel, the higher its amount of vital (= healthy) vegetation. The lower the NDVI, the more likely it is that a pixel hardly contains any vegetation – like in deserts or cities – or that there is only little vital vegetation – like after a forest fire or a storm.
In the coloured NDVI image of the Mediterranean above the vegetation-free areas of the Sahara stand out. You can also easily spot the mountainous regions of Mount Etna (volcano in Sicily) and of Mount Parnassus (Greek mainland) containing only very little vegetation. Can you detect any other differences in the spatial NDVI pattern?

 


Conclusion:

Remote sensing images cover the state of the vegetation worldwide. The special spectral fingerprint of green vegetation is used for analysis: Its reflection curve is characteristic, especially the transition zone between the red and infrared range where the slope of the curve increases rapidly. To analyse this quantitatively, statistical measures like the NDVI have been developed.