Earth Observation

Satellite Remote Sensing or Earth Observation is the collection of data concerning an object or any phenomenon without having physical contact with it.

In short

This field has numerous applications, like photography, topography, geology, forestry etc. In the field of agriculture in particular, Satellite Remote Sensing is widely used by an increasing number of applications worldwide, and it is combined with Big Data for smart data processing.

The Data Science methods and tools used by NEUROPUBLIC are state-of-the-art in the fields of Geo-Informatics and Artificial Intelligence. More specifically, Earth Observation with Data Science tools are used in agriculture in order to predict the expected crop efficiency and to determine the amount that will be harvested under specific conditions, as well as to identify crops and map them.

NEUROPUBLIC has developed an information system that maps different crops in Greece and generates statistical data regarding their geographical distribution.

Highlights

Smart applications

NEUROPUBLIC develops statistical analysis and machine learning models with the aim to develop “smart” applications for the agricultural sector. Furthermore, it utilizes a big volume of satellite images provided by the European Space Agency (ESA), in order to provide farmers and Public Agencies with smart observations and solutions. Particularly, these methods utilize full spectrum multidimensional data/images including spatial and temporal dimensions.

Farmers and Agronomists

NEUROPUBLIC innovates in this field too, as the integrated Informatics system we have developed that monitors the crops cultivated at parcel level provides irrigation, plant protection and fertilization advice to farmers and agronomists.

Organizations

The integrated Informatics system is addressed to organizations performing payments and controls according to European Union’s Common Agricultural Policy (CAP). It provides the possibility to monitor the agricultural land falling under their responsibility and to confirm the accuracy of producers’ data on two main points:

  • Monitoring and control of the correct geographical and spatial position of the declared parcel.
  • Confirmation of the declared crops per parcel.

The system provides the possibility for the aforementioned controls in a modern, mass and automated way, in large scale and with minimal human intervention.

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