Report from the Commission to the Council and the European Parliament on implementation of Decision No 1445/2000/EC on the application of aerial-survey and remote-sensing techniques to the agricultural statistics
Date: 2007-09-27
Institutions: European Commission
Subjects: agricultural statistics, application of EU law, crop yield, data collection, environmental monitoring, land use, management information system, meteorology, remote sensing

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COMMISSION OF THE EUROPEAN COMMUNITIES 

Brussels, 27.9.2007 
COM(2007) 552 final 

REPORT FROM THE COMMISSION TO THE COUNCIL AND THE EUROPEAN 
PARLIAMENT 

on implementation of Decision No 1445/2000/EC on the application of aerial-survey and 
remote-sensing techniques to the agricultural statistics 

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TABLE OF CONTENTS 

1. 

2. 

2.1. 

2.2. 

2.3. 

3. 

3.1. 

3.2. 

3.3. 

3.4. 

3.5. 

Introduction .................................................................................................................. 3 

The LUCAS project ..................................................................................................... 3 

Implementation ............................................................................................................ 3 

Resources used ............................................................................................................. 6 

Proposals on how areal-survey techniques could continue to be used......................... 7 

The MARS project ....................................................................................................... 9 

Purpose of the project................................................................................................... 9 

Methodology ................................................................................................................ 9 

Evaluation of the results............................................................................................. 10 

Conclusions ................................................................................................................ 11 

ANNEX 1 ..................................................................................................................... 12 

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1. 

INTRODUCTION 

Decision No 1445/2000/EC of the European Parliament and of the Council of 22 May 2000 
on the application of aerial-survey and remote-sensing techniques to the agricultural statistics 
for  1999  to  20031,  which  was  continued  until  2007  by  Decision  No  2066/2003/EC  of  10 
November  20032  and  extended  to  the  new  EU-10  Member  States  by  Decision  No 
786/2004/EC of 21 April 2004, required the Commission: 

-  to  implement  an  areal-survey  project  at  Community  level  in  agricultural  statistics  (the 
“LUCAS” project); and 

-  to  continue  the  use  of  remote-sensing,  in  particular  with  the  agrometeorological  system 
being made operational (the “MARS” project). 

This report has been drawn up pursuant to Article 6 of Decision No 1445/2000/EC and deals 
separately  with  implementation  of  both  these  measures,  with  the  resources  used  and  with 
proposals on how areal-survey and remote-sensing techniques could continue to be used. 

2. 

THE LUCAS PROJECT 

The  main  aim  of  the  LUCAS  pilot  project  is  to  test  the  feasibility  of  an  areal  survey  at 
Community level, specifically to:  

“– collect data needed to implement and monitor the common agricultural policy and analyse 
interactions between agriculture, the environment and the countryside, 

– provide estimates of the areas under the principal crops.” 

It  is  therefore  designed  to  obtain  harmonised  information  on  land  use  and  land  cover, 
especially  on  agricultural  land,  with  satisfactory  precision  at  EU  level.  It  also  aims  at 
collecting territorial information on the environment.  

2.1. 

Implementation  

2.1.1.  Activities undertaken 

The following activities have been undertaken since 2000: 

LUCAS surveys have been undertaken in 2001/02, 2003, 2006 (with a preparatory survey in 
2005), and 2007. The Member States covered are listed in Table 2.  

The initial LUCAS survey, split into two phases (an areal survey in the spring and a follow-up 
farm survey in the autumn), was carried out on around 100 000 points.  

A  new  methodology  (new  sampling  design  based  on  an  EU  grid  in  line  with  the  INSPIRE 
recommendations) was defined in 2004 when it was decided to abandon the follow-up farm 
survey in autumn, in the light of the negative experience in 2001-2003.  

For the sampling design of the survey (169 197 points in 2006), it was necessary to stratify by 
photo-interpretation the master sample points in the 2 km grid covering the territory of EU-25 
in  2005.  The  survey  focuses  on  agricultural  land,  with  an  initial  sampling  rate  of  50%  for 

1 

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OJ L 163, 4.7.2000, p. 1. Decision as last amended by Decision No 786/2004/EC (OJ L 138, 30.4.2004, 
p. 7). 
OJ L 309, 26.11.2003, p. 9. 

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arable land and for permanent crops and of 40% for grassland (all non-agricultural strata are 
also covered, with a sampling rate of 10% each). 

Following this methodology, surveyors observe the parameters on each geo-referenced survey 
point  in  the  field,  using  GPS  technology,  orthophotos  and  maps  to  localize  and  reach  the 
points on the ground. Depending on the focus of the survey, other characteristics besides the 
key parameters can be gathered (such as mapping transects or taking soil samples).  

A further LUCAS survey focusing on environmental variables such as erosion risk, irrigation 
and landscape features was carried out in spring 2007 on a sub-sample of points covered in 
2005/2006. 

Several studies have been launched on analysis of the survey results, on the potential of the 
LUCAS data for agri-environmental indicators, on the potential of aerial photo-interpretation 
for data collection, on use of photographs for landscape categorisation, on preparatory work 
for the future of LUCAS and on technology watch to improve the data-gathering process. 

2.1.2.  Main results 

The  main  results  of  these  activities,  in  response  to  the  requests  made  in  the  Decision,  are 
summed up below: 

The pilot surveys carried out in the Member States over the period 2001-2007 demonstrated 
the  feasibility  of  this  project  on  a  Community  scale.  General  advantages  of  the  LUCAS 
survey methodology approach are (1) high thematic precision, (2) high representativeness, (3) 
harmonized survey approach, (4) accurate change detection, (5) flexible survey structure, and 
(6) fast execution (up-to-date information).3  

LUCAS data have been collected in all the Member States listed in Table 2. The 2001-2003 
survey,  carried  out  in  EU-15,  includes  land  cover,  land  use  and  environmental  parameters 
(linear elements along transects, erosion, noise and hazards). The new methodology applied 
from the 2005 survey onwards and the reasons for the changes were described at length in the 
2005 special report on LUCAS4.  

The data collected over the period 2001-2007 allow analysis of time series for monitoring the 
common  agricultural  policy,  within  the  restrictions  due  to  changes  of  methodology  and  the 
limited coverage of the data samples. Interactions between agriculture, the environment and 
the  countryside  can  be  studied  by  evaluating  changes  in  land  cover/land  use  over  time  and 
along  the  mapped  transects,  but  also  by  analysing  the  environmental  parameters  surveyed 
(landscape recognition, erosion risk, irrigation, structural and linear elements, as surveyed in 
2007). 

Further relevant results obtained in the pilot phase include: 

•  a sound methodology, harmonised at EU level, proposing two-phase sampling of 

unclustered points, with stratification after the first phase5; 

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EFTAS,  SADL,  LUXspace  (2007):  Prospective  Study  on  potential  use  of  LUCAS.  Final  report  of 
Contract N°61103.2005.001-2006.157.  
Report from the Commission to the Member States on implementation of aerial-survey (LUCAS) and 
remote-sensing techniques (MARS) to the agricultural statistics. COM (2005) XXX. 
The systematic sample (base sample) is linked to a 1 km grid based on the INSPIRE recommendations 
and corresponds to around 4 million points for the entire European Union. 
The  LUCAS  master  sample  is  a  subset  of  the  base  sample  corresponding  to  a  2  km  grid  created  by 
using all the even points in the base sample and therefore consists of around 1 million points.  

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•  a  considerable  volume  of  data  and  photographs  (1.2  TB),  which  can  be  used  to 
measure changes in land use and land cover over time or as a sampling base for 
specific surveys; 

•  IT  infrastructure  which  is  operational  and  ready  to  be  used  for  future  surveys, 
consisting of hardware systems, a data warehouse, along with the software needed 
to collect the data, to check the data against the photographs and controlling their 
quality,  to  generate  the  samples  and  to  calculate  the  estimates  as  well  as  to 
recognize landscape diversity on the photographs taken, and to compare different 
grids used for areal surveys; 

•  solid experience in management of areal surveys. 

2.1.3.  Lessons learned from the pilot project and from the studies launched 

Estimates can be provided with the required precision at EU level. 

LUCAS provides information on agricultural areas but also on other land cover and uses, such 
as urban or forest data, in a consistent form for the whole of the EU. Precision is expected to 
be  around  or  better  than  2%6  for  the  main  categories  like  wheat,  cereals,  arable  land, 
permanent grassland, permanent crops, forests, urban areas or inland waters. Comparison with 
national  statistics  shows  good  consistency  for  arable  land  in  general.  At  lower  levels,  the 
consistency remains satisfactory for all cereals, common wheat, barley and maize (apart from 
in 2006 due to the late season and late sowing period). On smaller areas, the differences are 
proportional to the dispersion of the crops on the territory. 

Table 1 – Precision obtained by LUCAS for main land cover classes in 2001, 2003 and 2006 

2001 

2003 

2006 

Surface 
in % 

Precision error: 
CV (%) 

Surface 
in % 

Precision error: 
CV (%) 

Surface 
in % 

Precision error: 
CV (%) 

ARTIFICIAL 
LAND 

CROPLAND 

SHRUBLAND 

WOODLAND  

1.07
4.80
0.26
25.08
0.40
35.23
1.35
8.18
0.42
16.06
1.29
2.49
1.76
7.29
WATER 
NB: Surface changes of the land cover classes from 2001/2003 to 2006 are due to the different Member States 
covered by the respective surveys. 

5.62 
30.92 
28.83 
5.69 
23.25 
3.42 
1.70 

4.80
25.80
35.00
8.30
15.70
3.10
7.30

2.7 
1.3 
1 
2.9 
1.4 
5.3 
3 

2.2
1
0.8
2
1.1
3
2.1

GRASSLAND 

BARE LAND 

Ground photographs are of utmost importance for validation of the data. 

During  the  quality  tests  conducted  in  the  various  surveys,  it  became  clear  that  ground 
photographs taken by the surveyors (i.e. photographs of  landscape, the point and the cover) 
were extremely useful for checking, validating and, possibly, correcting the data gathered on 
the field. 

Each point in the master sample is photo-interpreted and then assigned to one of seven strata (“arable 
land”,  “permanent  crops”,  “permanent  grassland”,  “wooded  areas,  shrubland”,  “bare  land  and  low  or 
rare vegetation”, “water” or “artificial land”). From the stratified master sample, a sub-sample of points 
(field sample) is extracted to be classified by a field visit based on the established nomenclature. 
To allow comparison with the results provided by Council Regulations (EEC) No 959/93 on other crop 
statistics and (EEC) No 837/90 on cereals production. 

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It is difficult to carry out field surveys before May. 

During the 2006 survey an attempt was made to move the usual survey period between May 
and mid-July forward to March-June in order to provide crop area estimates by 15 June. Even 
if  early  estimates  can  be  supplied  by  mid-June,  the  results  are  heavily  influenced  by  the 
weather conditions and the stage of the agricultural season. Data inconsistencies could occur 
as a result of confusion between cereals in their early stages, over-representation of bare soil 
(on  late  sown  or  fallow  land)  or  flooding  or  inaccessibility  making  it  impossible  to  survey 
certain points. 

Points can be found again on the ground. 

With  the  help  of  GPS  technology,  photographs  from  earlier  surveys  and  maps  and 
orthophotos,  it  was  possible  to  find  all  the  points  correctly  surveyed  in  2006  on  the  ground 
once again in 2007.  

2.2. 

Resources used 

Table 2 - Expenditure incurred for the LUCAS surveys (in €) 

Description 

2001-2002 

2003 

2005  
(Phare 2003 
budget) 

2006 

2007* 

Quality assurance and 
documentation 
EU-25 stratification 
Belgium and Luxembourg 
Czech Republic 
Denmark 
Germany 
Greece 
Spain 
France 
Italy 
Latvia 
Lithuania 
Hungary 
Netherlands 
Austria 
Poland 
Portugal 
Slovak Republic 
Finland 
Sweden 
United Kingdom and Ireland 
Estonia, Hungary and 
Slovenia (Phare 2000) 

262 777 

199 713 

71 875 

271 651 

900 000 

44 597 
45 000 

65 065 
66 830 

747 000 

530 318 
983 528 
232 500 

238 727 
61 400 

78 254 

451 000 

94 640 

62 475 

47 361 

98 803 
403 936 
115 499 
227 149 
419 295 
180 488 

112 692 
339 329 
100 084 
228 053 
237 074 
147 028 

97 957 
157 808 

107 338 
129 669 

110 808 

92 801 

248 377 
511 470 
255 791 

447 500 

197 511 
329 470 
156 340 

NN 

NN 
NN 

NN 

NN 
NN 
NN 
NN 
NN 
NN 
NN 

NN 

NN 

3 600 133
* Breakdown by Member State not yet available 

TOTAL 

2 424 463

1 139 726

3 742 659 

700 000

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Table 3 - Expenditure incurred for the LUCAS methodological analyses (in €) 

Description 

COST 

Methodological analysis of the results of the 2001 LUCAS survey  

Study of the role of photo-interpretation in the LUCAS survey  

Study of the use of data from the Community’s LUCAS survey (2002-2004) 

Improvement of Phase 2 sample 

Multi-dimensional cross-analysis of LUCAS data (landscape classification) 

Prospective study on potential use of LUCAS 

Combination of multiple data sources  

Technology watch 

Total 

Table 4 - Expenditure incurred for the LUCAS IT infrastructure (in €)  

Description 

Servers, disk storage and backup system 

Workstations, screens, printers 

Development of the data entry tool 

Image processing software 

Database development, data warehouse 

Total 

90 200 

50 000 

463 790 

3 000 

280 000 

150 000 

42 500 

70 000 

1 149 490 

COST 

109 813.22 

8 203.77 

111 830.00 

36 587.00 

251 732.00 

518 165.99 

2.3. 

Proposals on how areal-survey techniques could continue to be used 

Main EU policy domains identified on which LUCAS can contribute are land cover/land use, 
landscape  diversity  and  structure,  soil  erosion  and  quality,  or  land  management.  For  policy 
domains such as air pollution, water quality and forest monitoring, LUCAS may support the 
legal  obligations  of  the  Member  States  through  data  harmonisation  and  accessibility  with 
relatively minor effort involved.7  

2.3.1. The available LUCAS data are potentially useful for a range of purposes: 

(a) Gathering agricultural and environmental data 

LUCAS could provide crop area estimates, independent of farm declarations, which could be 
of importance for CAP market management once fully validated and operational and when the 
other crop statistics are not fully developed or not fully reliable.  

It  can  also  be  used  as  a  sampling  base  for  more  specific  surveys  linked  to  agricultural  and 
environmental issues.  

It  is  one  of  the  very  few  identified  contributors  to  the  agri-environmental  indicators  on 
landscape and on changes in land cover. One major information gap that LUCAS can bridge 
is about the presence of linear features and landscape diversity all over Europe. 

7 

As concluded in: EFTAS, SADL, LUXspace (2007) see above.  

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It  can  be  considered  a  unique  source  of  basic  information  for  modelling  erosion  risk,  for 
surveying irrigation use and map landscape elements and for other environmental variables. 

(b) Providing data for landscape analysis 

The historical archive of landscape elements, environmental information and photographs is a 
valuable  source  of  baseline  information  for  future  trend  analysis.  LUCAS  provides  data  for 
long-term monitoring of agricultural and environmental issues on a European scale. 

Another  added  value  is  the  possibility  precisely  to  compare  the  observations  made  in 
successive surveys in order to detect differences and changes in land cover and land use.  

Combined with orthophotos and remote-sensing data, LUCAS provides insight into the spatial 
organisation  of  agriculture  and  the  balance  between  agriculture/nature  conservation/cultural 
heritage/green areas, etc. It provides an understanding of the size, location, connectivity and 
fragmentation of habitats, thereby supporting conservation and management of landscapes. 

(c) Linking the data with Earth observation projects 

LUCAS is expected to be one of the main “in situ” data providers needed for GMES (Global 
monitoring  for  environment  and  security8).  In  situ  data  at  EU-27  level  to  support  satellite 
research  are  required  for  the  space  work  programme  under  the  7th  R&D  Framework 
Programme. 

The CORINE exercise being carried out by the EAA has made and is making extensive use of 
LUCAS data and photographs. 

LUCAS  provides  harmonised  information  on  land  cover  and  land  use  in  a  consistent  form 
across  the  whole  territory  of  the  Union.  Such  land  management  information  systems  could 
turn into the backbone of the future European Spatial Data Infrastructure (ESDI). 

2.3.2.  The  strength  of  the  LUCAS  survey  is  based  upon  providing  data  for  combined 
agricultural and environmental policy needs rather than delivering crop estimates only: 

Each  individual  purpose  listed  above  can  hardly  justify  a  LUCAS  survey  on  its  own.  In 
particular,  crop  area  estimates  based  on  traditional  farm  declarations  exist  in  most  EU 
Member States;  

and  the  landscape  indicators  have  not  yet  been  properly  defined  and  the  Commission  was 
asked by the Council to take close account of the costs and resource implications of any new 
data collection initiative that goes beyond the existing legal requirements. 

On  the  other  hand,  results  of  modelling  efforts  or  remote  sensing  cannot  replace  in-situ  (or 
ground-truth) monitoring such as that performed by LUCAS. LUCAS could be defined as one 
of the European in-situ standards (e.g. within the INSPIRE initiative). 

2.3.3. Future LUCAS surveys 

A LUCAS survey is planned in BG and RO in spring 2008 as part of PHARE 2006. 

Additional specific LUCAS surveys might be carried out on request using the general LUCAS 
surveys as a sampling frame. 

Triennial LUCAS surveys could be carried out in 2009 and 2012 covering the whole EU in 
order to meet most of the needs identified above, avoiding double fieldwork. 

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http://www.gmes.info/. 

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3. 

THE MARS PROJECT 

3.1. 

Purpose of the project 

The  purpose  of  the  agro-meteorological  system  of  monitoring  crops  and  forecasting  yields, 
developed by the Joint Research Centre (JRC) as part of the MARS (Monitoring Agriculture 
with  Remote  Sensing)  project  within  the  Agriculture  Unit  of  the  Institute  for  the  Protection 
and  Security  of  the  Citizen,  is  to  provide  the  evidence  necessary  for  understanding  how 
climatic events have an impact on harvests and to forecast the yields of the main crops. The 
main result of this activitiy is the MARS Crop Yield Forecasting System which is operational 
since 1998.  

In  line  with  the  implementing  procedures  provided  for  in  Decisions  No  1445/2000/EC  and 
2066/2003/EC, the activities are aimed at activating both the agro-meteorological model and 
the  chain  for  processing  low-resolution  satellite  data  from  the  NOAA  and  VEGETATION. 
These data are used to analyse, monitor and forecast European field crop yields. The JRC has 
taken  on  the  task  of  maintaining  the  models  and  software  and  providing  overall  project 
supervision.  The  MARS  activities  include  other  specific  tasks  covered  by  the  Research 
Framework Programme, which are not further reported in this context. 

3.2.  Methodology  

The MARS Crop Yield Forecasting System comprises four activities:  

•  purchase of weather data and processing, calculation, interpolation and storage of 

derived weather data; 

•  use  of  the  weather  data  in  the  agro-meteorological  model  of  the  Crop  Growth 
Monitoring  System  (CGMS).  The  results  consist  of  a  series  of  indicators  for 
simulating  growth  of  the  main  crops.  These  indicators  are  stored  in  a  geo-
referenced  database  which  allows  production  of  thematic  maps  of  weather 
statistics and indicators for each crop;  

•  acquisition  of  NOAA-AVHRR  and  SPOT-VEGETATION  satellite  images  and 
processing of these data by systems defined and developed by the JRC. Indicators 
of  the  state  of  vegetation  are  calculated  by  incorporating  CORINE  Land  Cover 
(CLC) data; use of CORINE makes it possible to calculate vegetation indicators at 
land cover class level. This improves the analysis of agriculture vegetation classes 
using low-resolution satellite indicators; 

•  establishment, at the JRC, of a group of experts on statistical analysis of the data 
and quantitative forecasts using previous indicators and publication of short-term 
crop yield analyses and forecasts.  

The operational activities mentioned in points 1, 2 and 3 have been privatised. The contracts 
were awarded to an external consortium for the period 2000-2003 (MARSOP) and continued 
under a new legal basis in the form of the MARSOP2 contract for the period 2004-2007. The 
fourth activity referred to above (establishment of a group of experts on statistical analysis of 
the  quantitative  forecasts)  has  been  managed  directly  by  the  Commission  at  the  JRC,  in 
coordination  with  DG  Agriculture.  The  most  notable  result  of  this  activity  is  the  MARS 
Bulletin, of which 94 issues were published in the period 1999-2006, with twenty-one planned 
in 2007. The MARS Bulletins include analysis of the impact of climate on the main EU crops, 
including short-term weather forecasts, and are regularly used by DG-AGRI’s Outlook group 
of  analysts.  The  information  and  data  provided  are  used  to  support  the  CAP  decision-

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making  process:  i.e  food  balance  sheet  estimates,  budgetary  forecasts  and  follow  up  of 
expenditures,  stock  interventions  and  management,  export  tenders,  definition  of  set 
aside  rates  and  use,  support  to  EU  Markets,  etc.  Special  issues  on  ad-hoc  analyses  are 
produced  on  request  by  DG-AGRI.  The  results  emerging  from  the  operational  data 
processing are publicly available on the site http://www.marsop.info.  

As a consequence of the enlargement process and in order to scale up the MARS Crop Yield 
Forecasting  System  to  cover  25  countries  operationally  and  to  make  it  more  professional,  a 
number of activities were launched in 2004 under the ASEMARS project (Actions in support 
of the Enlargement for the MARS Crop Yield Forecasting System). These will continue up to 
2008. The project is divided into seven objectives, which correspond to seven lots: 

– 

– 

– 

– 

– 

– 

– 

Update of the CGMS: to complete and reinforce the Crop Growth Monitoring 
System on the new EU-10 Member States, calibrate the missing crops, include 
the new European soil map, use the Corine 2000 data set and introduce further 
automatic procedures in the statistical module of the CGMS.  

New  meteorological  data  sets:  additional  weather  stations,  data  based  on 
numerical  weather  models,  both  as  re-analyses  and  as  forecasts  (ten-day, 
monthly and seasonal) and agro-phenology data to complete and reinforce the 
MARS database used for the analyses.  

New  medium-  and  low-resolution  satellite  data  to  complete  and  reinforce  the 
MARS database used for the analyses, to calculate more precise satellite-based 
indicators,  to  produce  Meteosat  second-generation  data,  to  improve  estimates 
of the impact of frost and health stresses and to produce MODIS and MERIS 
data with better resolution (200-300 m instead of 1 km).  

A new operational CGMS, based on ensembles probabilistic weather forecasts, 
to make the CGMS system operational to run crop simulations on 10 days for 
intra-seasonal and seasonal weather forecasts and able to produce probabilistic 
crop yield forecasts.  

CGMS-Wofost  and  Lingra  calibration  platform  to  implement  crop  calibration 
systematically  and  in  a  controlled  way  in  order  to  update  and  maintain  the 
models both on crops and pasture and grassland.  

CGMS sensitivity analysis platform to implement a sensitivity analysis tool for 
system  validation  and  sensitivity  analysis,  with  the  purpose  of  improving 
modelling.  

Finally, a lot has been launched in the form of CMI in 2006, with the purpose 
of  collecting  agro-phenological  data  from  the  existing  national  services.  The 
data  are  needed  to  improve  calibration  of  models  and  consequent  analysis  of 
the simulations obtained.  

Table 5 (see Annex 1) shows the use of Community funding for the MARS-STAT projects in 
the periods 2000-2003 and 2004-2007.  

3.3. 

Evaluation of the results 

3.3.1.  The MARS Crop Yield Forecasting System 

The MARS Crop Yield Forecasting System has made it possible to evaluate the impact of the 
climate  on  yields  at  EU-25  level,  in  an  independent  and  homogeneous  manner  throughout 
Europe. 

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The  yield  forecasts  from  the  Bulletin  are  used  by  DG  AGRI  as  input  data  to  compile  the 
estimated balances for field crops for the European Union and for the applicant countries. 

Evaluation  of  the  forecasts  issued  is  a  permanent  activity  at  the  JRC’s  MARS  unit.  The  a 
posteriori errors in the quantitative yield forecasts are calculated from the final official data. 
For the period 1999-2003, the forecasting errors are not more than the average errors from the 
MARS  system  published  in  previous  years  (source:  QUAMP  report,  outcome  of  a  study 
financed by the JRC and carried out by an independent external company in 2003-2004). The 
root mean square error (RMSE) calculated for cereals showed an increase in the error in the 
forecasts after enlargement (from 0.6 q/ha to 1.5 q/ha). However, the trend in the RMSE has 
been sharply downward since the first few years of the ASEMARS projects (in 2005 the error 
decreased to 0.1 q/ha).  

3.3.2.  Additional research activities carried out by the JRC under its own research budget 
land  cover  estimation  methodologies 

and  related 
the  reinforcement  of 
(Institutional support to EUROSTAT for the LUCAS project) 

to 

Besides the agro-meteorological activities, other research projects limited to technology watch 
and  methodological  support  to  LUCAS  are  carried  out  by  the  JRC  and  financed  by  its  own 
budget.  

In  order  to  optimise  the  efficiency  of  the  LUCAS  sample  design  within  the  same  budget 
constraints, a modified methodology was tested in Greece, in response to a request from the 
Greek Ministry of Agriculture.  

The  results  confirmed  the  expected  improvement  in  precision  (coefficients  of  variation 
improved  by  a  factor  of  three),  following  the  adoption  of  the  modified  point  frame 
methodology.  Consequently,  the  survey  served  as  a  reference  for  drafting  the  specifications 
for the LUCAS 2005 and 2006 surveys. 

A second activity was the development of software for calculating the  LUCAS estimates in 
accordance  with  the  new  point  frame  methodology  (CAESAR  software).  The  software  was 
used for the LUCAS 2005 and 2006 campaigns. 

3.4. 

Conclusions 

In  the  light  of  the  usefulness  of  the  information  and  data  provided  in  support  of  CAP 
deployment  by  the  JRC  in  relation  to  MARS  in  recent  years,  the  Commission  wishes  to 
continue this activity over the period 2008-2013.  

EN 

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   EN 

 
. 

3.5. 

ANNEX 1 

Table 5 - Expenditure incurred for the agro-meteorological system (MARS-STAT) (in €)  

Lot/phase 

Phase 1 

Phase 2 

Phase 3 

Period 

LOT 1  
LOT 2  
LOT 3  
LOT 4  
Coordination  
Total/phase  

2000/2001  

2002  

2003  

151 812  
204 900  
207 294  
259 372  
74 220  
897 598  

99 650  
87 500  
160 010  
197 468  
29 500  
574 128  

99 650  
90 100  
162 310  
200 567  
30 400  
583 027  

Total 
(all 3 phases) 
2000/2003  

351 112  
382 500  
529 614  
657 407  
134 120  
2 054 753  

Table 6 - MARS expenditure from DG-AGRI budget line (commitment appropriations) based on renewal of the  
Council Decision for the period 2004/2007 and on the MARS OP II and ASEMARS projects schedule 

MARS commitments  
Project/year 

MARS OP II phase 1 
MARS OP II phase 2 
ASEMARS phase1 
MARS OP II phase 3 
ASEMARS phase2 
MARS OP II phase 4 
ASEMARS phase 3 
ASEMARS phase 4 
MARS OP II 
ASEMARS 
Total MARS 

2003 

850 000 

2004 

2005 

2006 

2007 

TOTAL 

595 751 
649 800

557 233 
650 000

850 000 

850 000 

595 751 
649 800 
1 245 551 

557 233 
650 000 
1 207 233 

600 000 
551 924

600 000 
551 924 
1 151 924 

647 492 

647 492 
647 492 

5 102 200

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   EN