The future of productive and profitable farming is continually being shaped by the introduction of precision farming principles. At Aquila Drones we can provide the farmer with some valuable remote sensing solutions, enabling him to make informed management decisions. At the forefront of the tools being offered is the proven vegetation health index maps known as NDVI. With NDVI stressed vegetation can be identified long before it has deteriorated to the point where is becomes visible. What is NDVI: Normalized Difference Vegetation Index (NDVI) quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs). By using the data gathered by multispectral cameras, we are able to calculate the index value and associated level of stress in vegetation.
The image below describes the light reflectance principles being used to establish plant health.
A short video summary of the principles and applied technology
Benefits of drone based NDVI vs Satellite based NDVI
There are two primary areas where drone based NDVI surveys outperforms satellite based solutions. The first area is detail or resolution. The typical resolution of free satellite based NDVI index maps are between 20 and 30 meters per pixel. What this means is that each single pixel of the NDVI image represents an area of 30x30 meters in the case of that resolution. Our drone based surveys deliver resolutions up to 2cm ground resolution. It is thus clear that it would be very difficult to evaluate anything the size of a single tree with satellite. The other challenge for satellite solutions are the correction factors for atmospheric conditions on the day of data capture.
Satellite does however has it advantages when it comes to very large areas like forests etc. The best illustration of this would be to compare the NDVI index maps of the same area done with satellite and drone based high resolution.
At Aquila Drones it was important to follow a scientific approach working with specialist both locally and abroad in developing both the aircraft and sensors we use, but also the software and processes. Over the past two years an extensive development and testing program has been followed where actual chlorophyll measurements and laboratory results were compared to our NDVI index maps. Our results showed a repeatable and consistent correlation.
Our services offered consists of varying levels of outputs that can be generated. Typically the steps involve the acquisition of reflectance data by using fixed wing aircraft capable of carrying specialized sensors as well as conventional colour sensors. The following step is the processing of the data and providing either the client or his agricultural specialists with the NDVI data.
There at two primary aerial data sets that can be collected.
The first is the common colour camera system which that can be used to compile a 3D map of the terrain with a high resolution ortho corrected image of the total survey area. This is then made available to the farmer to be imported into google earth providing an easy method to review historic surveys. An overlay of high resolution color imaging in google earth is shown below. From this data set the contour lines of the terrain can be generated.
The second data set is the NDVI sensor which gathers data both in the visible and invisible infrared spectrum. This data is then used to generate the NDVI index maps which provide the vegetation health data.
We are using the industry leading software PIX4D combined with in house developed solutions in order to generate accurate maps and NDVI results. We also have developed methods that allow for the comparison of two historic data sets irrespective of the level of sun irradiance at the time of survey (summer vs winter)
Results are made available electronically to the client shortly after the survey. A0 printouts are also available on request.
Long Term Monitoring
By following a special long term program the changes in a specific area can be monitored since our data allows for historic comparisons of data. For our index maps we typically select 5 categories for the index maps. We can thus monitor the hectares per section being monitored that is in each category and then ultimately plotting each subsequent survey on a graph. The coverage / leaf area index is also calculated. This allow the farmer to quickly evaluate how the block is progressing.