Agricultural analysis based on Copernicus data

Earth observation is a promising field with for helping to cope with integral problems such of sustainability of food production and environmental preservation.

Copernicus datasets, basis for  satellite-based agricultural analysis: data from several Sentinel-family satellites producing radar and visible light data with up to 10m resolution.


This Use Case, in sum, is expected to make a contribution in: 

  • Overall: to enable the users to make the most of PROCESS architecture, thanks to the open, generic APIs developed.
  • Agricultural analysis: to refine, steer and validate the behaviour of any Earth System modelling system in much more flexible way than today, with specific advances such as:
    • Improvement of models (i.e., identify deviations of the Earth System model outputs).
    • Fast in-depth diagnosis (i.e., predict the relative importance of upcoming observations in a specific application like forestry or biodiversity).
    • Focus on ad hoc analysis (i.e., separate the human impact from natural system’s baseline development).


  1. Copernicus’ huge amount of information (3PB/month from radar data and 4,5PB from visible light data) also leads to a multi-disciplinary problem requiring integrating simulation models.
  2. It is necessary to treat land surface processes and human interventions within one model.


Main goal of PROCESS for agricultural, Copernicus data-based analysis: an easy-to-use yet powerful solution for realistic simulation of natural processes and impacts of human interventions:

  • Enabling users to focus on analysis.
  • A trade off between few (but ) rigorous principles and maximum predictive power.


Techniques and procedures

  • Based on modelling framework PROMET (Processes of Mass and Energy Transfer) as a validation tool for services interfacing Copernicus data sets.
  • Use of Multi-Model Simulations linked with observational data, in a combined modelling of the macroscale carbon cycle, water and energy inputs, key nutrients in the soil , plant metabolism and human behaviour.


  • Configuration of input variables within the PROCESS portal (IEE).
  • Deployment of a PROMET run from the IEE on the  LRZ infrastructure.
  • Stage-Out of the output data via LOBCDER for the end-user.


Specific resources for the Use Case

Ad hoc infrastructure as an evolution of PROCESS architecture 

Tools: simultaneous use of processing and analysis elements:

  • Modelling
  • Simulation
  • Pattern recognition
  • Verification and dimension reduction for datasets’ management


For the field of activity

A combination of solutions for final users is available: 

  • A framework that allows the user to run its solution from the portal without exposing their source code.
  • A series of advanced techniques based on an agricultural analysis of Earth observation data available through a generic API and web-based interface to Copernicus data for:
    • Tight coupling of the modelling applications
    • Observational data
    • Simulation results with associated metadata

For the entire project

  • A standardized multipurpose interface solution and connection to the closed sourcemake.   
  • Stress-testing of advanced data analysis techniques to be applied to other fields.