Agri Kultuur September / September 2015 | страница 13

an index of the amount of leaf
area of the plant relative to
ground coverage. For this reason,
healthy plants that are less leafy,
such as potatoes, will give a lower NDVI than leafy crops, such as
barley. This needs to be kept in
mind, so that only like vegetation
is compared with like.
As an example, figure 2 shows an
NDVI photomap of a field of potatoes, flanked by barley. The
NDVI for the barley is clearly
higher than for the potatoes, yet
only the lower central area of the
potato field is actually stressed.
Alternatively, a low score on the
NDVI, when leaf area is not low,
indicates low chlorophyll content.
This is usually the result of low
nitrogen content in the soil, so
the soil can be tested for nitrogen
content. Should the nitrogen content be within acceptable ranges,
additional causes of stress could
be related to water source problems, pollutants, heat (abiotic
forms of stress) or microbial infestation, parasites or the influence of pests (biotic stress). These
are identified by ‘groundtruthing’, i.e. using the GPS referencing in the diagram to locate
the stressed area and conduct
observations, tests and analysis.
NDVI imagery has been shown to
be highly accurate in identifying
stressed areas. What is more, the
NDVI index will indicate a problem approximately 2-4 weeks before the problem is bad enough
to be visible to the naked eye.
This gives a valuable intervention
opportunity – remedial steps can
be taken early, before the problem spreads or worsens. Nitrogen, irrigation or other measures
can be applied only to the affected area, thereby allowing large
cost savings to the farmer.
It is this factor that leads to the

Figure 2: NDVI Potatoes (source: AgriDrone)

high return on investment to the
drone system. Over a few seasons
the cost savings will amount to
many times the initial investment
on the drone system, and the
maintenance costs and overhead
costs on the drone are minimal.
NDVI also accurately indicates biomass, which is a good predictor of
yield. This can also improve efficiency and save costs.
The beauty of NDVI imagery is that
it is applicable to any form of vegetation, even pine forests. It has
been applied to vineyards, mealies
(corn), wheat, barley, canola, potatoes, tomatoes, sugar cane, lucerne, olive trees, fruit orchards,
cabbage, poppies and lettuce,
among others. Besides commercial

crops, it has also been used to assess the quality of pasturage and
grazing in livestock farming. Environmental scientists are also able to
use the imagery to help analyse
damaged areas of wild vegetation
and monitor its recovery.
Versus Satellite Imagery
NDVI imagery can also be generated using satellite imagery, specifically from the LANDSAT service.
However, the resolution of this imagery is much lower than that of
drone NDVI and usually several
weeks late, meaning that timeous
intervention is not possible. Also,
the low resolution means that borders between fields – such as roads
and rivers, will affect the average
NDVI for the adjacent crops, lead-