Aplication of remote sensing in Foodie

1. 1www.foodie-project.eu
Aplication of remote sensing in FOODIE
Vojtech Lukas, Tomas Reznik, Karel Charvat Jr., Karel Charvat, Sarka
Horakova

2. 2www.foodie-project.eu
• Scenario C – Monitoring of in-field variability for site specific crop management
• development of stable monitoring system for effective identification of spatio-temporal
variability of crops and to use this information for optimization of the crop management
practices.

3. 3www.foodie-project.eu
Sc.C – Site Specific Crop Management
Periodic satellite remote sensing
• for identification of spatial variability and capturing the
dynamics of vegetation growth, both at medium level of spatial
resolution
• Suggested satellite survey is based on the free available data of
Landsat 8 or in 2015 launched Sentinel-2.
• The main information are vegetation indices NDVI and EVI
• The absolute values of VI, their relative to mean value of the
field and change detection will be implemented for assessment
of crop stands and delineating of management zones.

4. 4www.foodie-project.eu
Example of L8 dataset for Czech pilot farm
LC81900262015127LGN00LC81890262015200LGN00
LC81900262015143LGN00
= not reliable for planning of VRA
Cloud coverage
over farm area

5. 5www.foodie-project.eu
• Landsat 8 OLI
• 30m spatial resolution for MS; 16 days revisit cycle
• USGS EarthExplorer – at-sensor radiance data (geotiff)
• USGS ESPA – surface reflectance data incl. basic set of VI products
• Sentinel 2 A/B MSI
• 13 bands, 10m / 20m / 60m spatial resolution; revisit time 5 days (S2A+S2B)
• ESA Sentinels Scientific Data Hub
Data source

6. 6www.foodie-project.eu
Estimation of field crop
variability based on the recent
years Landsat images and EVI2
index
FOODIE Czech pilot farm

7. 7www.foodie-project.eu
Landsat 8 OLI images
 crop development within 68-ha (spring barley) and 62-ha
(winter wheat) fields in 2014 represented by NDVI

8. 8www.foodie-project.eu
Sc.C – Site Specific Crop Management
Operative aerial remote sensing
• mapping of the fields at high spatial resolution but with low frequency
• the aim is to prepare the prescription maps for variable applications of
fertilizers and pesticides, estimated by the spectral measurement of crop
parameters.
• aerial imaging will be carried out using multispectral camera (Ultracam) by an
external provider of photogrammetric services.
• a workflow will be developed for pre-processing of acquired images
(radiometric and geometric corrections) and their analysis and classification
according to the MJM interpretation algorithms.

9. 9www.foodie-project.eu
• Multispectral aerial imaging (Ultracam UCX)
winter wheat (69 ha)
Mai 2014

10. 10www.foodie-project.eu
Farm Telemetry

11. 11www.foodie-project.eu
Tractor Art

12. 12www.foodie-project.eu
• The effectiveness of each production, including agriculture, is determined by the
ratio of the value of the production outputs to the value of production inputs. One
of the possibilities of solving the farm effectiveness problem,
• FarmTelemetry focuses on is to optimize the level of farm inputs. It can be the
energy needed to power agricultural machinery on the fields, energy for the
transport of inputs and outputs of production
Farm Telemetry

13. 13www.foodie-project.eu
Machinery Monitoring

14. 14www.foodie-project.eu
Machinery monitoring

15. Tractor movement

16. Fuel consumption: tillage (l/h)

17. Fuel consumption: detail (l/h)

18. Work Log: Excel export

19. Daily time utilization (Excel export)