COMMISSION STAFF WORKING PAPER Accompanying theREPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL on the implementation of the remote sensing applications and on the use of the financial resources made available to it under Council Regulation (EC) No 78/2008 (second interim report)Background information in the form of graphs and maps on the Mars Crop Yield Forecasting System and details on the outputs made available
Date: 2011-10-10
Institutions: European Commission
Subjects: agricultural statistics, common agricultural policy, crop yield, meteorology, remote sensing

EUROPEAN COMMISSION 

Brussels, 10.10.2011 
SEC(2011) 1170 final 

COMMISSION STAFF WORKING PAPER 

Accompanying the 

REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND 
THE COUNCIL  

on the implementation of the remote sensing applications and on the use of the financial 
resources made available to it under Council Regulation (EC) No 78/2008 (second 
interim report) 

Background information in the form of graphs and maps on the Mars Crop Yield 
Forecasting System and details on the outputs made available 

{COM(2011) 639 final} 

 
 
 
 
  
 
 
 
 
 
The purpose of the present document is to provide additional information on the functioning 
of the Mars Crop Yield Forecasting System (MCYFS) and the different outputs prepared by 
this activity. It accompanies the Report from the Commission to the Council and the European 
Parliament on the implementation of Council Regulation (EC) No 78/2008 and provides in the 
form  of  illustrations,  graphs  and  maps,  additional  information  on  the  architecture  and  the 
functioning of the system together with information on the various outputs and reference to 
websites. 

1. 

GENERAL SYSTEM SET-UP AND WORK FLOW 

Figure  1.  MCYFS:  sketch  showing  the  main  input  data  and  the  main  tasks  carried 
out by the analysts 

Figure  2.  Main  building  blocks  of  the  system.  The  system  consists  of  four  main 
building blocks which are integrated to monitor crop behaviour and produces yield 
forecasts 

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Figure 3. Countries covered by the European window of the MCYFS (in green) for 
the crop yield forecasts and agro-meteorological analysis 

2. 

METEOROLOGICAL INFRASTRUCTURE 

Figure  4.  Overview  of  meteorological  infrastructure:  input  data;  indicators; 
database extraction; information extraction over space and time 

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Figure  5.  Meteorological  station  network  with  daily  data  reception  (e.g.  rainfall, 
temperature). The data is stored in the system and further interpolated to a grid with 
a resolution of 25km x 25 km 

Figure  6.  Outputs  from  the  meteorological  infrastructure  used  for  the  analysis. 
Example of maps and graphs on minimum daily temperature and rainfall compared 
to the long-term average and graphs based on observed meteorological parameters 
from the station network 

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Figure  7.  Outputs  from  the  meteorological  infrastructure  used  for  the  analysis. 
Examples  of  maps  based  on  weather  forecast  data:  average  daily  temperature; 
longest heat wave period; numbers of days with rain; cumulated precipitation 

3. 

CROP MODEL INFRASTRUCTURE FOR THE SIMULATION OF CROP GROWTH 

Figure  8.  Overview  of  the  crop  model  infrastructure:  input  data;  crop  growth 
simulation; indicators; information extraction over space and time 

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Figure  9.  Examples  of  outputs  from  the  crop  model  infrastructure  used  for  the 
analysis  in  the  form  of  maps  and  graphs:  crop  development  stage;  heat  waves 
around  crop  maturity  dates;  crop  specific  relative  soil  moisture;  potential  storage 
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4. 

LOW RESOLUTION SATELLITE DATA 

Figure 10. Overview of remote-sensing infrastructure: satellite sensors used as input 
data; pre processing and computation of vegetation state; meteorological indicators; 
information extraction over space and time 

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Figure  11.  Examples  of  meteorological  indicators  produced  by  the  remote-sensing 
infrastructure: mean temperature; solar radiation; frost days; snow cover 

Figure  12.  Examples  of  vegetation  state  parameters  used  for  the  analysis  and  the 
crop yield forecasting process: the Normalized Difference Vegetation Index (NDVI) 
as an indicator for biomass 

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5. 

STATISTICAL ANALYSIS 

Figure  13.  Overview  of  the  statistical  infrastructure  used  to  produce  the  yield 
forecasts: input data, tools and methods applied 

Figure 14. Example of crop yield forecast estimates provided at EU 27 level 

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6. 

INFORMATION DISSEMINATION 

Figure 15. Crop monitoring bulletins for Europe 

Figure  16.  Screen  shot  from  the  existing  web  portal  offering  weather  indicators, 
crop indicators and vegetation indices based on remote-sensing data 

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Internet resources 

•  Web  portal  for  information  dissemination  and  links  to  the  bulletins  and 

distribution of meteorological data upon registration:  

http://www.marsop.info/marsop3/ 

•  Access to the crop monitoring bulletin for Europe, the European pasture bulletin, 

the European rice bulletin, climatic updates and forecasts updates:  

http://mars.jrc.ec.europa.eu/mars/About-us/AGRI4CAST/MARS-Bulletins-for-
Europe 

•  Access to remote-sensing imagery for vegetation monitoring: 

http://cidportal.jrc.ec.europa.eu/home/idp/thematic-portals/agri4cast-imageserver/ 

•  General information concerning the activity and related work: 

http://mars.jrc.ec.europa.eu/mars/About-us/AGRI4CAST 

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