Creating a vegetation index (NDVI) from XCAM RGB-NIR

Taking advantage of some downtime between projects for an XCAM RGB/NIR unit, we flew GeoXphere's home town of Basingstoke to see what we can produce with the latest processing software.

Our weapon of choice for this survey was an XCAM with a normal RGB sensor and a NIR-modified sensor. With these two sensors we'd be able to use the Red, Green, Blue and NIR band to produce an NDVI index map... so that's what we did.


About NDVI

If you'd like a detailed explanation of NDVI (Normalised Density Vegetation Index) then read the wikipedia page. In a nutshell, it's a measure of the chlorophyll response from vegetation. Healthy and lush vegetation gives a high response (up to +1), unhealthy or weak vegetation give a low response (down to 0). Anything with a negative value has no response at all and is therefore not vegetation or dead. (also consult a biologist for a better description).


The Survey

The survey was planned at 7cm GSD and used the Track Pattern method for flying straight survey lines with a high overlap. We covered 5 square kilometres (1.9 square miles) of the centre of Basingstoke, UK. The aircraft was on-site for just under 45 minutes.



Here was our processing method:

  1. Produce RGB and NIR orthophotos through Pix4D.
  2. Create an NDVI index map using Pix4D. (this isn't a very good explanation, but it's really easy to do).
  3. We then, as an extra step, ran the RGB imagery through Skyline Photomesh. We wanted to compare the two orthophotos. (Our preference for the orthophoto dataset was the Photomesh version, so we ended up with an excellent orthophoto and an NDVI index).
  4. Take the NDVI index, remove all the negative values and colorise the positive ones with NDVI colours. (Some NDVI maps also include the negative ones, but we wanted to overlay the two datasets so we got rid of that data).



We ended up with a set of GeoTIFF images for both the orthophoto and the NDVI map:


We weren't doing this survey for any particular purpose, but there are a range of applications here, such as:

  • How green is your city? A general analysis of the amount of vegetation in populated areas can be useful for planning of new developments and quantifying the amount of green space in each neighbourhood.


  • Detecting disease. By analysing the trees with strong responses versus weak ones, it's possible to identify the spread of disease. This data can then be used to put management schemes into action.


  • Micro-urbanisation. This is the trend of individuals converting their gardens and driveways from green spaces into man-made surfaces. This can have huge implications on surface water run-off and flooding.#


  • Archaeology. The patterns in the ground can reveal features that aren't immediately obvious from the true-colour aerial photography.




Interactive Data Showcase

Use the sliders below to overlay and remove the NDVI index.


Can you spot the small patch of artificial grass in this scene?


Some tree species are performing better than others. (caveat: I'm not an arboriculturalist so seek advice from a qualified adult if you need to know more).


No hidden features here, but you can see that the differences are accentuated.


Even the painted lines in these fields show as a different index response.



There are many applications for NDVI maps. If you'd like more information or want to commission an aerial survey of your area of interest then get in touch. They aren't a difficult dataset to work with, they can be fed directly into XMAP or other GIS systems using XMAP Feeds. This gives everyone in your organisation access to the data.


XCAM RGB-NIR is an aerial survey system built by WaldoAir. You can lease or purchase a pod for yourself, or GeoXphere can do it as a service for you (depending on your part of the World).

Skyline Photomesh is a dense-image matching processing software that has built-in aerotriangulation and outputs orthophoto, DSM, DTM, and 3D model data. It can be purchased from Skyline UK or GeoXphere can process projects for you as a service.