NUESTRAS SOLUCIONES

Our solutions

Precision agriculture

Home > Enviromental sustainability

Sector: Enviromental sustainability

Activity: Earth observation

Disciplines: Maps, remote sensing and artificial intelligence

Remote sensing techniques can offer farmers direct assistance in the control of their crops’ condition, furthermore, providing technology endowed with a highly superior cost / benefit ratio compared to other ground monitoring techniques.

From COTESA, we offer a wide range of precision agriculture products, such as the monitoring of crop states and conditions, determining the hydric needs of the soils or the automatic rating of large-scale farming projects. To achieve this, we have combined the information received from optical and radar satellites, applying to the latter the most recent trends in artificial intelligence and machine learning.

Main features of the service

Application of Sentinel-2 super-resolution imaging techniques to be able to calculate spectral indices featuring a resolution of 2.5 m

Calculation of optical vegetation (NDVI, BAI, EVI, etc) and radar indices (polarimetric and interferometric coherence indices) to determine crop status.

Construction of time series and phenological crop studies

Incorporation of meteorological variables and soil characteristics

Our products allow for crops to be classified as to determine their status and calculate hydric needs.

Other products: automatic plot detection, harvesting detection or automatic detection to changes in rural areas

Benefits

  • The use of super-resolution allows for vegetation indices to be obtained that are vastly superior to its native counterpart.
  • The incorporation of radar data allows us to offer solutions in regions with major cloud cover.
  • Remote sensing techniques allow for gradings of crops in large regions to be carried out at low cost.
  • Time series studies enable comparisons to be drawn with previous years to assess crop productivity.
  • Owing to the fact that the algorithms have been wholly devised by COTESA, these can be tailor-made to adapt to clients’ needs.
  • The use of super-resolution allows for vegetation indices to be obtained that are vastly superior to its native counterpart.
  • The incorporation of radar data allows us to offer solutions in regions with major cloud cover.
  • Remote sensing techniques allow for gradings of crops in large regions to be carried out at low cost.
  • Time series studies enable comparisons to be drawn with previous years to assess crop productivity.
  • Owing to the fact that the algorithms have been wholly devised by COTESA, these can be tailor-made to adapt to clients’ needs.

Success story

TRASGSATEC

TECHNICAL ASSISTANCE SERVICE FOR THE UNDERTAKING OF WATER NEEDS DETERMINATION FOR SPANISH IRRIGATION OVER THE YEARS 2019 and 2020, using tools based on the SIAR network, assisted by remote sensing devices with information provided by the programme COPERNICUS (Sentinel-2) and GIS, while consolidating findings from 2018, based on the FAO-56 model.

 

AGROSEGURO

Pilot project for the automatic determination of crops as a feasible alternative to ESYRCE surveys through the use of remote sensing techniques. To accomplish this, machine learning algorithms based on optical images and radar were applied.

Technological elements used

The products developed by COTESA are grounded on the application of artificial intelligence algorithms (Machine Learning and Deep Learning) implemented in the sphere of agriculture. Super-fine satellite image technology (based on Deep Learning) allows us to create products that best adapt to agriculturalists’ needs.

Thanks to the analysis of time series and phenology, our Machine Learning algorithms developed in Python are able to grade crops with success rates in excess of 90%.

More information

Miguel Fiz Fuertes
Jefe de Proyectos. Consultoría y Estudios