Multispectral imagery is a technique which gathers Near Infrared (NIR) as well as visible light in an image.
Healthy plants reflect far more NIR than visible light, so for any pixel in the image, the difference between the intensity of NIR and visible light can indicate the health of the plants, or the presence of plants versus soil. This can be used to monitor the health of a crop, or to detect weeds.
By calculating this difference for every pixel in the image, we can generate a monochrome (black & white) image where the brightness of each pixel represents the degree to which there is healthy vegetation. To make the differences more visible, the brightness levels can be converted to a colour-based representation of plant health. This is called colour mapping. As an example, green can represent vigorous growth, while red can represent absence of vegetation. Intermediate colours would represent varying degrees of plant health.
This technique, which we use, can be broadly called Vegetation Index. It appeared in the late ’70’s using multispectral imagery from Landsat satellites. There are many different implementations of this technique, which vary according to which visible band is used for the calculation, and which mathematical formula is used. The most well-known is Normalized Difference Vegetation Index (NDVI).
In Agriculture, this technique can identify problem areas in a crop before they are visible to the naked eye.
In Natural Resource Management, this technique can be used to detect weeds, as well as algal blooms in aquatic systems.