Aplication of remote sensing in Foodie

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Aplication of remote sensing in FOODIE

Vojtech Lukas, Tomas Reznik, Karel Charvat Jr., Karel Charvat, Sarka Horakova

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• 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.

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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.

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Example of L8 dataset for Czech pilot farm

LC81900262015127LGN00LC81890262015200LGN00

LC81900262015143LGN00= not reliable for planning of VRA

Cloud coverage over farm area

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• 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

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Estimation of field crop variability based on the recent years Landsat images and EVI2 index

FOODIE Czech pilot farm

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Landsat 8 OLI images crop development within 68-ha (spring barley) and 62-ha

(winter wheat) fields in 2014 represented by NDVI

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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.

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• Multispectral aerial imaging (Ultracam UCX)winter wheat (69 ha)Mai 2014

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Farm Telemetry

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Tractor Art

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• 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

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Machinery Monitoring

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Machinery monitoring

Tractor movement

Fuel consumption: tillage (l/h)

Fuel consumption: detail (l/h)

Work Log: Excel export

Daily time utilization (Excel export)