*This page introduces the scientific background of NDVI and its application to the [PLOTS visible/infrared camera tool](/wiki/dual-camera-kit-guide).* ![Par_action_spectrum.jpg](https://i.publiclab.org/system/images/photos/000/000/324/medium/Par_action_spectrum.jpg)

_Figure 1. The absorption of different wavelengths of visible light by photosynthetic pigments and the resulting spectral response of photosynthetic rate. Leaves appear green because the pigments do not absorb green wavelengths and reflect them all back for us to see. Modified from [here](http://en.wikipedia.org/wiki/File:Par_action_spectrum.gif)_ Vegetation is green because plant leaves reflect green light -- they don't use it for photosynthesis (Figure 1). Instead they use almost all of the blue and red wavelengths in sunlight. The pigments in leaves absorb this light to power photosynthesis which converts CO2, water, and nutrients into carbohydrates (food). In general, you can estimate the productivity or vigor of vegetation by how much blue and red light it is absorbing. Photosynthetic pigments do not use the longer, invisible wavelengths of infrared light and reflect almost all of it away (this helps prevent the leaves from overheating). About a year after the launch of the first Landsat satellite in 1972, scientists began using the data from its sensors to estimate the productivity of vegetation by comparing the amount of red light reflected (there is not much from healthy plants) to the amount of near infrared light reflected (there is a lot). The amount of infrared light reflected from vegetation is a good indicator of how bright the sunlight was at any moment (leaves reflect all IR), and comparing that to the amount of reflected red light can tell us what proportion of the sunlight was being absorbed by the plants. ![NDVI_is_eq.jpg](https://i.publiclab.org/system/images/photos/000/000/325/medium/NDVI_is_eq.jpg)






Kodacolor film IR transmission

Figure 7. Spectral transmission of exposed and developed Kodacolor negative film. All visible light is blocked, and most near infrared light passes through. This type of filter replaced the IR block filter in the Canon A495 cameras modified for the PLOTS KickStarter campaign. Data from: http://www.northcountryradio.com/Articles/irfltr.htm

_Figure 7. Spectral transmission of exposed and developed Kodacolor negative film. All visible light is blocked, and most near infrared light passes through. This type of filter replaced the IR block filter in the Canon A495 cameras modified for the PLOTS KickStarter campaign. [Data from here.](http://www.northcountryradio.com/Articles/irfltr.htm]_ An early goal of work with the PLOTS infrared camera kit is to learn how interpretable its version of NDVI is. Figure 3 suggests that the red and IR bands produced by the cameras are wider than the satellite bands commonly used. The red band probably extends into the green wavelengths (which plants reflect along with IR), which could complicate the interpretation of the NDVI values. There may also be some overlap of the red and IR bands, although the exact spectral response of the normal and modified Canon A495 cameras is not known. Maybe the PLOTS spectrometer can be used to determine the width of the bands being captured by the cameras. To compute NDVI, information about red light reflected from vegetation (recorded by the normal camera) must be combined with information about reflected near IR light (recorded by the modified IR camera). This must be done for the same patch of vegetation, and ideally for each pixel in the pair of rectified images. Rectifying the two images (aligning them on top of one another) may be impossible to do perfectly, so each image could be downsampled (adjacent pixels are combined and their color information averaged). That will reduce the chance that the calculation of NDVI uses red data from one area of vegetation and IR data from another area, a situation which could produce meaningless values. When two images of the same scene (one with a visible red channel, and one with a near IR channel) are ready (downsampled and rectified), photo manipulation software (Photoshop, GIMP) or image analysis software (ImageJ, Fiji) can be used to compute NDVI using the brightness values of red and near infrared light for each stacked pixel pair. The resulting new image can represent more productive vegetation with distinctive colors and make it possible to detect patterns of spatially varying plant vigor in the scene. By repeating the mapping process at different times, it is possible to detect changes in plant vigor over the seasons or from year to year.