About ThirdEye

A key factor in enabling an increase and efficiency in food production is providing farmers with relevant information. Such information is needed as farmers have limited resources (seed, water, fertilizer, pesticides, human power) and are always in doubt in which location and when they should supply these resources. Interesting is that especially smallholders, with their limited resources, are in need of this kind of information. Spatial information from Flying Sensors (drones) can be used for this. Flying Sensors offer also the opportunity to obtain information outside the visible range and can therefore detect information hidden for the human eye (Third Eye). Nowadays, low-cost sensors in the infra-red spectrum can detect crop stress about two weeks before the human eye can see this.

The Third Eye project supports farmers in Mozambique by setting up a network of Flying Sensors operators. These operators are equipped with Flying Sensors and tools to analyse the obtained imagery. Flying Sensors have been proven to provide useful information in supporting farmers. However, this project is unique as it is a first trial in a developing country to supply information on a regular base using Flying Sensors. At the end of the project (2017) we foresee that 8000 farmers will use our services, farmers’ yield will be increased by at least 10%, and farmers have improved their irrigation practices.

Results

  • 14 local Flying Sensor operators have been trained and obtained their certificate.
  • 11 Flying Sensors are now operational.
  • Over 3,500 farmers receive our service, of which 71% is female.
  • The number of people benefitting is over 17,000.
  • ThirdEye’s service area is over 1,600 ha.
  • Water productivity is increased by 55%, meaning more crop per drop.
Training new operators in the field.
Training new operators in the field.

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Our Technology

Flying Sensors

A Flying Sensor is a combination of a flying platform and camera. Reliable Flying Sensors are on the market in a wide-range of categories each with its specific characteristics. Based on the consortium’s experiences over the last years low-cost Flying Sensors have been identified that are excellent equipped for our innovation. Typically a Flying Sensor flies at a height of 100 meter and overlapping images are taken about every 5 seconds. This results in individual images covering about 50 x 50 meter and an overlap of 5 images for each point on earth. So in order to cover 100 ha 500 images are taken during a flight.

The use of Flying Sensor is unique and no comparative techniques exist that provide farmers with real-time high-resolution information. The use of satellites to provide farmers with spatial information has been promoted but has three main limitations: they have fixed overpass times, the spatial resolution is low, and the presence of clouds halters the information. It is unlikely that, within the coming decades, progress in satellites will be real competitors of Flying Sensors. Another category of comparable techniques to provide farmers with information is the use of ground sensors. Typical examples of these sensors are soil moisture devices, soil sampling and laboratory analysis, crop sampling and laboratory analysis. However, all those sensor techniques have the common limitation that information is only local point representative, while the main question farmers have is regarding to spatial differences. Moreover, these ground sensors are in all cases too expensive to be used by small-scale farmers.

We trained several Flying Sensor operators, who are going to the fields on a daily basis to gather information with their Flying Sensors and advice farmers on potential interventions they could take. These operators are able to support over 400 small-scale farmers, by collecting information and sharing it with farmers on weekly basis. Based on the information, farmers take decisions on where to do what in terms of irrigation, fertilizer application and pesticides.

This Flying Sensor is equipped with infrared sensors that detect crop stress about two weeks before the naked eye can observe this.
This Flying Sensor is equipped with infrared sensors that detect crop stress about two weeks before the naked eye can observe this.

NDVI technology

With our NDVI technology damaged plant material can be distinguished from healthy plant material.

When light falls on a leaf, reflection occurs. The amount of reflection of green light (0.54 µm) is very high, making plants green to the human eye. Healthy vegetation does not reflect much red light (0.7 µm), since it is absorbed by chlorophyll abundant in leafs. In the near-infrared spectrum (0,8 µm) the amount of reflection increases rapidly to 80% of the incoming light. This increase is caused by the transition of air between cell kernels. This is characteristic for healthy vegetation.

Damaged plant material does not show this increase in reflected near-infrared light. Moreover, the reflection of red light is much higher than in healthy plant material. By measuring the reflection in these spectra, damaged plant material can be distinguished from healthy plant material (Schans et al., 2011).

Our Flying Sensors have cameras which can measure the reflection of near-infrared light, as well as visible blue light. These two parameters are combined with a formula, giving the Normalized Difference Vegetation Index (NDVI). This information is delivered at a resolution of 2×2 cm in the infra-red spectrum. Infra-red is not visible to the human eye, but provides information on the status of the crop about two weeks earlier than what can be seen by the red-green-blue spectrum that is visible to the human eye.

NDVI is the most important ratio vegetation index and says something about the photosynthesis activity of the vegetation. Moreover, NDVI is an indicator for the amount of leaf mass, and therefore, ultimately biomass. In general, open fields have a NDVI value of around 0.2 and healthy vegetation of around 0.8. NDVI values give an indication of crop stress. This can be caused by a lack of water, lack of fertilizer, pests or abundancy of weeds.

Advice
Providing advice to farmers with near-infrared NDVI crop monitoring maps.

Our Team


Dr. Peter Droogers
Project leader
Dr. Peter Droogers is general director of HiView and FutureWater. Peter has over 15 years of experiences in water resources, vegetation monitoring, remote sensing and GIS.

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Jan van Til MA
Project manager
Jan van Til (MA) is operational manager of HiView. Jan is a BNUC-S certificated pilot of remotely piloted aircrafts (RPAs). Managing several HiView projects has made him an experienced field officer.

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Martijn de Klerk MSc
Project manager
Martijn de Klerk (MSc), project manager and hydrologist at FutureWater, is an environmental scientist with lots of experience in planning and organizing projects. He worked both as a consultant and scientific researcher.

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Nadja den Besten MSc
Field Manager
Nadja den Besten (MSc) is a hydrologist specialized in socio-hydrological modelling, water management, catchment response analysis and international project participation and management.

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Sam van Til MSc
Operatorational Manager
Sam van Til (MSc) is originally an architecture engineer but he familiarised himself with all technical aspects of the flying operations and is now our operational manager for the teams in Xai-Xai and Chókwè, also providing training.

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Gijs Simons MSc
Scientific Advisor
Gijs Simons (MSc) is a hydrologist with over five years of working experience in managing and executing international projects in the fields of water resource management and remote sensing.

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Dr. Walter Immerzeel
Scientific Advisor
Dr. Walter Immerzeel has seventeen years experience in geo-informatics, water resource management and climate change and is skilled in hydro-meteorological monitoring, remote sensing, simulation models and spatial analysis.

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Romeo Morello
Business Developer
Romeo Morello is marketing and administrative representative at HiView.

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Dercio Roberto Chissaque
Senior Flying Sensor Operator
Dercio Roberto Chissaque is working as senior flying sensor operator in Xai-Xai, Mozambique.





Nordino Justino Fijamo
Senior Flying Sensor Operator
Nordino Justino Fijamo is working as senior flying sensor operator in Chókwè, Mozambique.

Nelson Cossa
Senior Flying Sensor Operator
Nelson Cossa, a water user associations manager, is working as senior flying sensor operator in Chókwè, Mozambique.

Dalton Jonas Munguambe
Flying Sensor operator
Dalton Jonas Munguambe is working as flying sensor operator in Xai-Xai, Mozambique.





Milton Paulao Tomas Valoi
Flying Sensor operator
Milton Paulao Tomas Valoi is working as flying sensor operator in Chówkè, Mozambique.

Vania Dulce Macula
Flying Sensor Operator
Vania Dulce Macula is working as flying sensor operator in Chówkè, Mozambique.

News

FutureWater releases new study on monitoring Water Productivity

Water Productivity, expressed as the amount of crop yield over the amount of water consumed (kg/m3), has been accepted as the standard to monitor sustainable water management. FutureWater has evaluated various methods, including satellites and Flying Sensors (drones) to monitor Water Productivity for a demonstration project ThirdEye in southern Mozambique. Monitoring Water Productivity is set …

MSc thesis research on efficient use of water in agriculture: visiting Xai-Xai, Mozambique

Increasing world population, rising food demand, limited water resources. Currently 70% of the fresh water uptakes are already used for irrigation. The need for efficient water use in agriculture is undisputed! The United Nations’ Sustainable Development Goal 6.4 is set at the improvement of efficient use in order to reduce water scarcity and maintain food …

Field visit on monitoring water productivity in Quelimane, Mozambique

To follow up a good practical example of a our Masterclass on Water Productivity, our colleague Nadja den Besten went on a mission to Quelimane in Mozambique. FutureWater was invited to assess project APROVALE, Água Produtiva no Vale do Zambeze, in the Zambezi Valley. The project is led by Agencia de Desenvolvimento do Vale do Zambeze (ADVZ), …

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