NDVI and NRG
NDVI

NDVI stands for "Normalized Difference Vegetation Index". NRG stands for "Near-infrared / Red / Green". NDVI and NRG are both ways to visualize the amounts of infrared and other wavelengths of light reflected from vegetation. Because both these methods compare ratios of blue and red light absorbed versus green and IR light reflected, they can be used to evaluate the health of vegetation. It's a snapshot of how much photosynthesis is happening. This is helpful in assessing vegetative health or stress. (Read more here: https://www.agronomy.org/publications/jeq/articles/36/3/832) ## Do-It-Yourself These techniques for vegetation analysis were developed for satellite imagery, but at Public Lab, we've been working a lot on capturing infrared imagery using our DIY [near-infrared camera](/wiki/near-infrared-camera) setup, and combining it with visible bands to produce NDVI images such as the one above. ## What these images mean What exactly are these images we're trying to make? What do they tell us about vegetation, and why? These diagrams should help to understand what it is we're doing and why these are good ways to analyze plant life. ## The NDVI equation [![NDVI_is_eq.jpg](/i/44723)](/i/44723) **NDVI = (Near Infrared - Red)/(Near Infrared + Red)** NDVI is a ratio which tries to emphasize photosynthesis while filtering out sun glare. The above equation is run for every pixel, using source data from an infrared photo and a visible light photo, like this pair: [![5390895115_c9d4d38fec_o.jpg](https://publiclab.org/system/images/photos/000/021/771/large/5390895115_c9d4d38fec_o.jpg)](https://publiclab.org/system/images/photos/000/021/771/original/5390895115_c9d4d38fec_o.jpg) The result can be false-colored to make the high-photosynthesis areas more clear, and used to examine where plants are and how healthy they are. [![PetVISNDVIcomp.png](https://publiclab.org/system/images/photos/000/021/770/large/PetVISNDVIcomp.png)](https://publiclab.org/system/images/photos/000/021/770/original/PetVISNDVIcomp.png) _Figure above: Normal color photo (right) and normalized difference vegetation index (NDVI) image (left). NDVI image was derived from two color channels in a single photo taken with a camera modified with a special infrared filter. Note that tree trunks, brown grass, and rocks have very low NDVI values because they are not photosynthetic. Healthy plants typically have NDVI values between 0.1 and 0.9. -- @cfastie_ ### Activities Here are a range of activities you can do to produce and interpret your own NDVI imagery, whether downloaded from a satellite imagery provider or [collected yourself using a DIY technique](/wiki/multispectral-imaging) [activities:ndvi] **** ![IMG_0511-split.png](https://i.publiclab.org/system/images/photos/000/000/279/medium/IMG_0511-split.png) ![infrared-combination.png](https://i.publiclab.org/system/images/photos/000/000/278/medium/infrared-combination.png) Most DIY converted cameras today (those from Public Lab) use RGN instead of NRG, so the blue channel represents infrared instead of the red channel. That looks like this: [![rgn-split.png](/i/45468)](/i/45468?s=o) **** ## NRG imagery Some people are also interested in producing NRG imagery (like the below image), where `Near-Infrared, Red, and Green` are used to compose a picture instead of the usual `Red, Green, and Blue`. [![5415783775_502f79ac8c_o.png](/i/25064)](/i/25064) This diagram explains the swapping, which allows us to 'see' infrared as if it were a normal color: [![5396083368_40528d3da2_o.png](/i/25063)](/i/25063) **In NRG images, the deeper and clearer the red color, the denser and healthier the vegetation (more or less).** ### Questions [questions:ndvi] ### Other examples of DIY NDVI imaging From around the internet: Begin watching at 2 minutes to see the resulting imagery: *This topic is part of the [Grassroots Mapping Curriculum](/wiki/mapping-curriculum) series.* **** [![5416397210_5e3be40cf5_o.png](/i/25066)](/i/25066) [![5412520298_93873f36d0_o.png](/i/25065)](/i/25065) ...


Author Comment Last activity Moderation
warren "WOW!!! Was that generated onboard the Pi, or in post-processing? @xose @imvec take a look! " | Read more » about 6 years ago
maykef "Instant trigger in both cameras: " | Read more » about 6 years ago
maykef "CM Module carrier board designed for the multispectral camera. " | Read more » about 6 years ago
warren "Hi, I think that would be great. I'm trying to do an install of infragram in one recipe here, and if that works, I may do the same for image-sequen..." | Read more » about 6 years ago
maykef "Hi @warren, I like #image-sequencer. It would be very interesting to develop a variation of it customised for aerial imaging. It would have to incl..." | Read more » about 6 years ago
warren "Hi! This is awesome. You can find some more on related projects at #pi-camera and #raspberry-pi-infragram We're also working on a cool project to ..." | Read more » about 6 years ago
maykef "Hi MaggPi, Thanks for your comment. Picamera has a very simple de-mosaic algorithm. The way I've been analysing the images is by load them directl..." | Read more » about 6 years ago
MaggPi "It would be amazing if you could do this. I tried to capture RAW data but could never figure out how to de-mosaic, color balance and scale from 1..." | Read more » about 6 years ago
Aezys "What I’d like to do is taking some pictures with the NoIR camera, process them and then write some code in Python to get the percentage of healthy ..." | Read more » about 6 years ago
ARMann "@warren - its probably a MAPIR Survey 3 camera: https://www.mapir.camera/collections/survey3 " | Read more » about 6 years ago
cfastie "That's too bad about the proprietary Mapir calibration. Is there information about the spectral reflectivity of the calibration targets? If not, th..." | Read more » about 6 years ago
mrodriguezorejuela "@cfastie Thanks for your detailed explanation, that helped a ton! I do have the calibration targets from Mapir, unfortunately I need to assemble ou..." | Read more » about 6 years ago
DaleHCook "Although this thread is a bit old I discovered it while working on a somewhat related project, and thought I'd offer a few observations based upon ..." | Read more » over 6 years ago
cfastie "the camera collects red, green and nir channels So this camera has a red filter and captures NIR in the blue channel. The light in the chamber is..." | Read more » over 6 years ago
warren "Hi, can you share an image that you've taken with this camera? Where did you get the camera? Cool! " | Read more » over 6 years ago
warren "I posted an activity for doing NDVI-like work using a camera like this -- with a coefficient (on the output of NDVI, so like "boosted" NDVI) here: ..." | Read more » over 6 years ago
kayrufty "Very interesting post! NDVI is correlated with chlorophyll pigments, correct? Different phytoplankton types have different concentrations of chloro..." | Read more » over 6 years ago
juvinski "@juvinski awards a barnstar to khufkens for their awesome contribution! " | Read more » over 6 years ago
cfastie "MaggPi you are correct that presenting color-mapped data-based images without presenting the colormap key makes the images mostly meaningless to vi..." | Read more » over 6 years ago
warren "Yes! I think @tech4gt is working on this very soon! There's an issue open for it too. " | Read more » over 6 years ago
cheneyshreve ":smiley: " | Read more » over 6 years ago
MaggPi "Wow, thanks for the great response! I did this fairly quickly and I will try to catch up with the questions: did you illuminate these separate..." | Read more » over 6 years ago
cfastie "MaggPi, This approach is quite intriguing. You are correct that NDVI was invented and then used for 40 years primarily for high altitude aerial or..." | Read more » over 6 years ago
warren "@warren awards a barnstar to Claytonb for their awesome contribution! " | Read more » over 6 years ago