The latest Earth observation technology allows day-to-day satellite data application in various fields of agricultural activities. Thanks to our extensive experiences obtained in various research and commercial projects in the past the agricultural applications can be rated as one of the key activities of our company.


Crop type identification

Crop type identification and mapping has a number of important aspects. It can serve for production statistics together with yield prediction, mapping soil productivity, assessment of crop damage and monitoring of farming activities. These include identifying the crop types (winter and spring cereals, rapeseed, sugar beet, potato, maize, grass, etc.) and delineating their parcel extent. Crop type identification is often based on multitemporal, multispectral high resolution imagery, while parcel boundaries delineation is more often based on very-high resolution imagery.
Traditional methods of obtaining this information are statistical estimates or ground surveying. Remote sensing offers an efficient means of collecting the information, in order to map crop type and acreage. Remote sensing can also provide state information about the health of the vegetation. The spectral reflections vary with respect to changes in the phenology and crop health. This can be measured and monitored by multispectral sensors. Interpretations from remotely sensed data and geographic information system (GIS) combined with ancillary data provide information of ownership, management practices, etc. This approach can be used e.g. in agricultural subsidy controls.
Crop type identification and mapping is based on use of multitemporal imagery to enhance the classification by taking into account changes in reflectance as a function of plant phenology. This in turn requires calibrated sensors and frequent repeat imaging throughout the vegetation season.

Thematic services:
  • crop maps
  • map of crop canopy health
  • statistical figures of crop acreages


Crop growth development monitoring

Crop growth development monitoring by means of remote sensing and simulation models give main indicators for quantitative yield predictions. Remote sensing data (e.g. middle resolution) with daily acquisitions serve as a main source of vegetation indicators. Often NDVI (Normalized Differential Vegetation Index), DMP (Dry Matter Production) and other indicators are calculated in time series (daily or decadal composites) to monitor crop growth. Detailed spatial and time analysis results in yield predictions. Crop growth and soil water mechanistic simulation models can be employed in order to receive complementary information on crop growth development. These indicators provide information on potential and limited crop growth given a local meteorological and soil conditions calculated for different parameterized crop types. Assimilation of remote sensing parameters into simulation models enhances the analysed crop indicators. Prediction of drought can be based on both, purely remote sensing measurements but also on employing simulation models.
Final quantitative yield prediction can be also based on both sources of crop indicators. The scale of the output statistics depend upon the scale of input data (remote sensing images, meteorological data, soil maps, etc.) but also more notably on scale of collected reference measured yields. Yield prediction together with acreage estimates is used for production statistics.

Thematic services:
  • maps of vegetation indicators
  • analysis of vegetation development
  • drought monitoring
  • crop yield prediction (national / regional)


Precision Farming

Precision farming (or agriculture) is a new technology that allows farmers to adjust for within-field variability in a number of characteristics like soil fertility and weed populations. The use of global positioning system (GPS) to identify position within the field in the real time is one of the technological key elements. With the information of the position and on-board sensors, farm equipment can guide applications of crop inputs like fertilizers and herbicides or monitor crop yields. Precision farming has the potential to reduce costs through more efficient and effective applications of crop inputs. It can also reduce environmental impacts by allowing farmers to apply inputs only where they are needed at the appropriate rate.
Remote sensing is one of the main sources of the information on the crop and soil spatial variation with the fields. Several biophysical variables can be derived from RS images to assess degree of spatial variation as well as producing categorical maps separating parts of the fields according to the crop status.

Thematic services:
  • segmentation of vegetation cover (airborne and satellite images)
  • segmentation of yield maps
  • application maps preprocessing
  • geostatistical analysis of spatial variation
  • sampling optimisation


Relevant projects

Acronym Name / Duration Customer
CwRS Remote sensing control of agricultural area-based subsidies
2004 - 2013 State Agricultural Intervention Fund (Czech Republic)
MARSOP3 Operational activities for MARS actions – Period 3
2008 - 2013 Joint Research Centre (DG JRC) / Alterra (Netherlands)
G-MOSAIC GMES Support to security applications
2009 - 2012 EC FP7 / e-Geos (Italy)
geoland2 GMES Land Monitoring services
2008 - 2012 EC FP7 / Astrium GmbH (Germany)
SAFER GMES Emergency response and development support
2009 - 2012 EC FP7 / Infoterra FR SAS (France)
LPISQC LPIS Quality Assurance
2010 - 2011 Ministry of Agriculture of the Czech Republic
WATERPROTECT Multidisciplinary assessment of the effects of territorial protection of important sites for water management in the Czech Republic
2010 - 2011 Czech University of Life Sciences Prague, Faculty of Environmental Sciences / Ministry of Agriculture of the Czech Republic
ETC-LUSI European Topic Centre on Land Use and Spatial Information
2006 - 2010 European Environment Agency (EEA)
RESPOND GMES Emergency response and development support
2007 - 2010 European Space Agency (ESA) / Infoterra UK (United Kingdom)
GSE Land GSE Land Information Services
2007 - 2009 European Space Agency (ESA) / Infoterra DE (Germany)
ASEMARS Actions in Support of the Enlargement of the MARS Crop Yield Forecasting System
2005 - 2008 Joint Research Centre (DG JRC) / Alterra (Netherlands)
CROPMAP Agriculture land mapping for pesticides monitoring in the hydrosphere
2007 - 2008 Czech University of Life Sciences
REAL Remote sensing identification and monitoring of abandoned land
2007 - 2008 Czech Ministry of Education
PAST Analysis of the new monitoring and control requirements related to the permanent grasslands
2006 - 2007 Joint Research Centre (DG JRC) / SADL (Belgium)
SBC Sugar beet production control with remote sensing
2005 - 2007 Moravskoslezské cukrovary a.s. / EKOTOXA (Czech Republic)
DAIFOR Development of agro-environmental indicators for assessment of rural landscape changes
2005 - 2006 Flemish programme for Central and Eastern Europe (Belgium)
GMES SAGE SAGE (Service for the Provision of Advanced Geoinformation on Environmental Pressure and State)
2005 - 2006 European Space Agency (ESA) / Infoterra Germany
WILDLIFEDMG Using satellite data for monitoring damages on agricultural areas caused by wildlife
2005 - 2006 IFER (Czech Republic)
RAID RAID Feasibility Project Nr. 2 – Cross-compliance GeoPortal
2005 Joint Research Centre (DG JRC)
PREFARM Assesment of spatial variability of agricultural fields by means of yield and satelite image data
2004 AGROFERT (Czech Republic)
ERSAPP Application of ERS data in agriculture and topography
2000 - 2003 Europan Space Agency (ESA), Czech Ministry of Education
IACS Integrated administrative and control system (IACS) in the Czech agricultural sector
2000 - 2003 Czech Ministry of Agriculture / EKOTOXA Opava (Czech Republic)
MOCA Crop monographies on EU candidate countries
2003 Joint Research Centre (DG JRC)
MARS Remote sensing application for agricultural statistics
1992 - 1999 Czech Ministry of Agriculture, Joint Research Centre (DG JRC)
AGRISARDEM Application of the satellite SAR data for DEM generation and crop discrimination
1997 - 1998 Europan Space Agency (ESA), Czech Ministry of Education
MERA CGMS MARS Environmental Related Applications - Agrometeorological modeling
1995 - 1996 Join Research Centre (JRC) Ispra, Czech Ministry of Agriculture