Remote sensing in agriculture, an indispensable tool

Remote sensing or remote sensing has made it possible to prevent, manage or predict agriculture in a more realistic way.

The next chapter of the book “Mediterranean Horticultural Technology: Evolution and Future” has been written by the specialist Francisco Jose Garcia,  Universitat Politècnica de Catalunya. It details what were the beginnings of remote sensing in agriculture, the great advantages they offer in the prevention, management and prediction of certain events or actions, and future perspectives regarding their use.

Remote sensing or remote sensing has achieved that currently, in agriculture, it can be prevented, managed or predicted in a more realistic way.

Its beginnings go back to small experimental plots of vines in Australia, where the growth of the crop was measured to determine the optimum moment of harvest or the management of its growth.

Subsequently, starting in the 90s, the development exponential of technologies with high resolution multispectral cameras allowed to improve the use of remote sensing and the results obtained for the monitoring of agriculture.

The complementarity of tools

Currently, although they are still used satellites With much higher resolution and review speed applied to large-area crop extensions, it is true that there is another complementary and increasingly used tool, the drone. The application of the drone is limited to intensive crops and small areas, generating and analyzing data with much more detail than a satellite or an airplane.

Main uses of remote sensing

Undoubtedly, remote sensing plays a fundamental role in current agriculture, and among the main and advantages that it offers, we can highlight the determination of the variability of the crop for the valorization of the harvest, irrigation management, variable fertilization and early detection of pests and diseases.

Final conclusions

It is indisputable that the use of remote sensing brings a huge number of benefits to agriculture such as accurate and real data, although we still have to continue working on the "analysis and interpretation" of these data so that the farmer can take advantage of them in a more effective way.

Regarding the analysis tools, the systems currently offer data and help the technician who is the one who finally makes decisions based on their interpretation, but in the future, it is expected that the tools themselves make their decisions under an autonomous criterion and pre-established by the technicians.

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