Unmanned aircraft
Systems (UAS) are supposed to bring big advantages for the usage in farm-scaled
applications. These applications are expected to help achieving a sustainable
agriculture. The UAS provide the characteristics of data acquisition demanded
by the farmers, for example small pixel size or coverage on demand even if
there are clouds. Furthermore, it offers a quick delivery of information and
that while being cheaper. In all these points satellite based systems or manned
aircrafts, mostly used by governmental organisations, failed before.
UAS make
precision agriculture achievable, because by being provided exact soil data,
farmers are able to calculate accurately where and how much fertilizer is
needed. Today, fertilizer is in fact applied in an amount suitable only for
areas with the highest yield potential. UAS can also be used to measure crop
growth by sending Near Infrared radiation (NIR) to the ground and detecting the
reflected radiation, an advantage, although remote sensing is not essential.
There are many other systems available, but the adoption of these technologies
is slower than estimated and it’s depending a great deal on the farmer and the
size of the farm. Only a small part of the farmers will be able to use UAS,
particularly the ones already using variable rate technologies. And the
question whether the technology will result in economic and environmental
benefit is yet to be answered.
UAS can not
only be used for measuring crop growth, but also for taking high resolution
images, to detect spatial variability of water stress and to manage irrigation
more effectively. Water stress can be measured with thermal sensors, which are
still quite expensive. Methods calculating the amount of water used for
irrigation include spectral vegetation indices and plant canopy temperature
measurements. Another advantage of UAS are the smaller ground sample distances.
Imagery taken form UAS close to the ground can be used to identify the soil
between rows of crop, using object-based image analysis. Also, germination
rates can be determined with pixel counting, using imagery with even smaller
ground sample distances, between 0.5 and 2.5 cm. Furthermore, accurate crop
height can be calculated by the difference between the digital surface and the
actual ground elevation model delivered from orthomosaic images.
A big
problem of measuring soil and plant properties with spectral reflectance is the
second-to-second variation of atmospheric transmittance. It can be solved with
up-looking sensors to measure the variation in incident light levels directly.
These measurements can be used to calibrate cameras and multispectral sensors
instantly.
Remote
sensing with UAS has three niches in precision agriculture: scouting for
problems, monitoring to prevent yield losses and planning crop management
operations. Using nutrient management as an example, ‘scouting’ checks to see
whether a specific area has a nutrient deficiency, ‘monitoring’ systematically
searches for areas that may need more nutrients, and ‘planning’ determines the
economically optimal fertilization rates. But regarding the costs of processing
data by professionals only the ‘scouting’ may be economically reasonable. UAS
have a big potential to detect weed occurrence, disease outbreaks and insect
infestations due to the small ground sample distance. However, the accuracy of
identification is still not high and therefore the best treatment can’t easily
be determined(Hunt & Daughtry,
2018).
In summary
it can be said that the potential of remote sensing with UAS in precision
agriculture is high, but not yet in every aspect competitive. Nevertheless,
with more automatized data analysis and advanced processing the advantages of
UAS could outrun the negative aspects.
Sighted
literature:
Hunt, E. R. J. &
Daughtry, C. S. T. (2018). What good are unmanned aircraft systems for
agricultural remote sensing and precision agriculture? International Journal of Remote Sensing, 39 (15–16), 5345–5376.
https://doi.org/10.1080/01431161.2017.1410300
