How is remote sensing used in precision agriculture and what is the NDVI index? How is plant health assessed with a drone and why do drones “see more” than the human eye? Find out what a prescription map is and how it helps reduce crop production costs.
Assessing plant health with remote sensing
Remote sensing is based on the ability of observed objects to reflect, absorb and transmit electromagnetic waves. For surveys from low altitude, the most commonly used are passive sensors, i.e. sensors that record waves from a natural source of radiation – the Sun.
Plants reflect electromagnetic waves in a particular way, which is caused by several factors, mainly water, pigments and cellulose. Visible light (400–700 nm) is controlled by the pigments in the leaves, such as chlorophyll and carotenoids. Chlorophyll absorbs most strongly in the blue and red parts of the spectrum. Reflection is highest for wavelengths corresponding to green, which is why people see leaves as green. The human eye, however, cannot see the condition of the internal structure of the leaf, which affects infrared waves outside the visible spectrum. In the near infrared – NIR (780–1400 nm) – the outer layers of plants are transparent, which allows the waves to penetrate deep into the structure.
Because of the way plants reflect red radiation (absorption) and near-infrared radiation (reflection), a number of indices have been developed that use these wavelengths to assess plant health. The most popular is NDVI (Normalized Difference Vegetation Index) – the normalised difference vegetation index. It ranges from -1 to 1, where negative values correspond to areas without vegetation and positive values depend on vegetation density and vigour.
NDVI in practice
The way plants reflect radiation can be used in practice for agricultural purposes: to assess plant health and plan fertilisation. To calculate the index, the measurements of red and NIR reflection mentioned above are needed. They are recorded as images with spectral sensors on satellites or aircraft. With drone measurements, the images are free of the atmospheric scattering of waves, and the low flight altitude gives a high resolution. An orthophoto map is created from the individual images and the NDVI index is calculated.
The finished colour images showing the index values are already useful for visual analysis of the surveyed area. They make it possible to identify parts of the field that need special attention, for example areas that are under-fertilised.
Using the index to create prescription maps
Once the cause of poorer plant health has been identified, the next step can be to create a prescription map. It is used for variable-rate fertiliser application, a core element of precision agriculture. It contains information on the condition of the plants and the planned optimal amounts of fertiliser to feed them. The benefits of using a prescription map:
- Correct and even plant nutrition across the whole field,
- Lower costs – optimal fertiliser doses are spread precisely, which saves product,
- Faster work,
- Reduced negative impact of agriculture on the environment
Creating a prescription map consists of the following stages:
- Survey flight – during which photos of the selected field are taken.
- Image processing – an orthophoto map is created from the collected photos. Thanks to the GNSS receiver on board the aircraft, the orthophoto map is fitted to the geographic coordinate system.
- NDVI calculation – the vegetation index is calculated.
- Generating the prescription map – based on the NDVI values, the field is divided into zones that need a higher or lower dose of fertiliser. Set amounts of fertiliser are assigned to the index values.
- Uploading the prescription map to the farm navigation system and fertilising.
If you have a farm navigation system and a fertiliser spreader, using a prescription map is very simple. Just have it made by specialists and agree on the required amounts of fertiliser. Upload the map to the navigation system and the machine will do the rest.
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