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Home - Case study: Drones give data, visibility to French farming cooperative
Data AnalyticsInternet of Things (IoT)Smart FarmUse cases

Case study: Drones give data, visibility to French farming cooperative

by Phillip Tracy August 29, 2016
written by Phillip Tracy August 29, 2016 Share
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source: senseFly
68

Drones used in precision agriculture

OCEALIA Group is a French farming cooperative with 7,200 members and nearly 900 employees. Since 2015, five drone operators have been flying the group’s two AIRINOV multiSPEC 4C sensor-equipped SenseFly eBee Ag drones in order to gain valuable fertilization data.

“The drone data is complementary to satellite imagery, which we still use for the general monitoring of our members’ crops throughout the year,” said Romain Coussy, manager of decision support tools at OCEALIA. “However, for providing quick tips on fertilization, the drone is best adapted to the job. By using the drone for aerial crop scouting, combined with data processing and analysis from AIRINOV, plus our complementary controls, we can provide members with fertilization advice between 48 hours and four days after a flight.”

source: senseFly

source: senseFly

Since 2015, OCEALIA’s two drones have been used to help over 300 individual farmers, flying over 3,900 ha (9637 ac) of oilseed rape and 3300 ha (8,154 ac) of cereals like wheat, barley and triticale.

“As agronomy experts, our role at AIRINOV is to help OCEALIA’s farmers increase their yields and improve the quality of their crops – mainly cereals and oilseed rape,” said Romain Faroux, CEO and co-founder of AIRINOV. “We do this by analyzing imagery with a strong agronomic approach that goes way further than typical NDVI maps. This enables us to provide reliable advice to optimize the application of nitrogen. It’s about applying the right amount of nitrogen, at the right time, in the right place in the field. Lastly, on top of using our fertilization advice, OCEALIA’s technical and agronomist teams use the maps produced to improve their knowledge of their farmers’ fields and so better advise them.”

How the drones were used

OCEALIA’s drone team typically flies once or twice per season for each farmer who requests the service.

The devices fly at an altitude of 150 meters above the ground and capture their images using AIRINOV’s multiSPEC 4C camera. According to senseFly, the flight height and camera capabilities result in an image resolution on the ground of approximately 30 cm per pixel. This data is then downgraded to one meter per pixel for large fields in order to speed up delivery time. In terms of field coverage, the drones map crops at a rate of around three hectares per minute, depending on field size.

source: AIRINOV

source: AIRINOV

The multiSPEC 4C camera is a multi-spectral sensor that was designed specifically for use with senseFly’s eBee drone. It captures non-visible data of crops over four distinct spectral bands: green, red, red-edge and near-infrared. AIRINOV then processes this imagery into maps that allow the company’s agronomists to give a precise crop assessment for every square meter of a farmer’s field.

The drone’s data is used to measure the amount of dry matter in the field and nitrogen absorption at key stages of the crop’s development, according to senseFly. For farmers looking solely to increase yield, a flight takes place when the crop is between Z30 and Z33 stage, while for those looking to boost crop quality—i.e. increase the amount of protein in the plant—the flight instead takes place at Z39 stage.

“Farmers can choose to get a drone flight at any stage,” said Coussy. “The flight is then planned about a week before fertiliser application and the data used to variably apply the season’s third and fourth fertiliser inputs.”

For oilseed rape, OCEALIA’s team flies the drones once at the start of winter and once at the end in order to calculate the amount of biomass lost.

“This figure tells us a lot about the size and strength of the crop, as well as the amount of nitrogen that has not been absorbed since the farmer’s previous application,” Faroux said. “The aim again is to advise a farmer how much fertiliser to apply. This recommended amount is then usually applied in two or three different inputs during spring.”

Data and analysis

To generate its recommendations, AIRINOV’s agronomists apply different algorithms to the drone’s digital crop maps.

In the case of oilseed rape for example, AIRINOV measures biomass development and combines this with other field data (soil type, variety etc) to make fertilization recommendations with square-meter precision.

source: senseFly

source: senseFly

For cereals, AIRINOV measures dry matter and nitrogen absorption in the field to assess the real growth potential of the crop, since taking a single approach like measuring only biomass or assessing only NDVI, has not proven to be precise nor robust enough to make reliable fertilization recommendations, says senseFly.

AIRINOV supplies the farmer with two variable application maps featuring its nitrogen recommendations. One map is a detailed version, designed with automatic application in mind, for farmers who operate advanced precision agriculture equipment. In this case, the farmer receives a file by email that is compatible with their equipment. The second map is a simplified version, which is better suited to farmers who apply their nitrogen manually or using less advanced equipment.

Thanks to both types of map being supplied, any farmer can begin variable rate application, whatever equipment they operate.

The results

“The OCEALIA farmers who have used our AIRINOV-supported drone service have recorded an average yield increase of 10%, compared to parcels analysed using traditional, non-drone methods,” said Coussy.

source: senseFly

source: senseFly

“This boost in yield is obviously of great value to OCEALIA’s members,” Faroux said. “While it would not be accurate for every client to expect this kind of boost—since yields depend on so many variables: from the weather to the type of soil and a 3 plant’s particular traits—OCEALIA’s results are a solid, real-world example of how drone data and expert algorithmic analysis can have a real beneficial effect on farmers’ businesses.”

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Table of Contents

  • Drones used in precision agriculture
  • How the drones were used
  • Data and analysis
  • The results
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