Precision farming | icgc

Precision farming

The ICGC selects the parameters to observe and the techniques to apply in precision farming

Imatge aèria d'una zona agrícola.

Agriculture is linked to food, and the continuous increase in world population suggests an optimization of related resources. Thus, in areas where water is scarce, only those parts that really need it could be watered, and the same would happen with nitrates and fertilizers.

At the same time, it is possible to improve the yield of crops and increase the quality of the resulting products, through specific monitoring of various parameters, such as water stress. This monitoring also allows the detection of diseases and reduces their effects.

In fact, some countries already apply precision agriculture techniques, from the measurement and analysis of the conditions that occur in the crop, to the automatic navigation of the machinery.

Apart from these productive improvements, the detection and control of varieties, such as olive and grape varieties, favors a fair distribution of administrative aid to farmers, and a correct compliance with the rules established by appellations of origin, especially wines.



This data collection can be done in the field, thus achieving a high degree of reliability and facilitating the diversity of information. Unfortunately, the efficiency of this option in large areas of land is low, and its validity is almost null when the measurements are carried out in a reduced time window.

An alternative would be, then, the use of airborne observation sensors or on-board satellites, taking into account their resolution in each case and the type of information that can be obtained.

It must be said, however, that the results of the previous solution can be optimized, complementing it with observations in the field, since it would be possible to calibrate and review the results in question, in addition to the knowledge of new variables.

In any case, the data processing and its subsequent analysis are essential in obtaining relevant results, requiring significant statistical knowledge and prior experimentation.


Solution description

The ICGC has hyperspectral and thermal sensors that allow a data capture configured according to the requirements that arise, especially in terms of spectral and spatial resolution. Furthermore, extensive experimentation has been carried out with these and the parameters to be taken into account are well known.

Preliminary calibrations and additional measurements are usually carried out in the field, in order to obtain precise results, in addition to increasing the knowledge of variables such as the spectral response of different plants in different situations, and thus training the system.

It should be noted that the ICGC evaluates each case, taking into account the various aspects of precision agriculture, and then selects the parameters to observe and the techniques to apply pertinently, planning several flights if necessary (as in studies where evolution phenological or the diversity of climatic conditions are relevant).

For example, for the detection of varieties, it is usually calculated NDVI, transforming the images into main components, evaluating statistical indices (Hellden, Short, Kia ...), etc. On the other hand, to control water stress in order to improve the quality of a product, empirical models such as the so-called baseline or the energy balance equation can be used, once variables such as temperature have been measured.

It must be said that, in general, several sensors (hyperspectral and thermal) are used to have as much data as possible and facilitate tasks such as crop discrimination.

On the other hand, joint work with entities specialized in the different types of crops facilitates the analysis of the data in some of the applications.

Imatge aèria d'una zona agrícola amb dades hiperespectrals i tèrmiques.





O. Viñas et al., Revista de Teledetección, 2009.

Tree Species Classification from Aerial Images and Lidar in Agricultural Areas

A. Ruiz et al., Setmana Geomàtica, 2009.

M. Torre et al., ISPRS Amsterdam, 2000.



Fulfilled projects

  • Detection of grape varieties in La Rioja.
  • FARMSTAR: optimization of organic resources in cereal fields. France.


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