Securing Water for Food: Grand Challenge for Development
Approximately 2.8 billion people – 40% of the world’s population – live in river basins impacted by water scarcity. Of those impacted, 1.2 billion people live in areas of physical water scarcity, where demand is greater than the available supply. Another 1.6 billion people face economic water scarcity, where institutional, financial and human factors limit access to water despite an available natural supply.
Between 2000 and 2050, water demand is projected to increase by 55% globally, meaning that the number of people impacted by water scarcity will continue to rise. Furthermore, 70% of all global water use occurs in the food value chain. By 2050, 45% of total GDP ($63 trillion) will be at risk due to water scarcity. We are at pivotal moment when we face unprecedented challenges to food security and the preservation of our global environment.
The Securing Water for Food Grand Challenge for Development is harnessing the forces of science and technology to develop solutions to water scarcity. The program is funded by USAID, the Swedish government (Sida), and the Dutch government (MFA-NL). The overarching goal of Securing Water for Food is to enable the production of more food with less water and/or make more water available for food production, processing, and distribution.
FutureWater has been granted support from the Securing Water for Food Grand Challenge for Development for piloting the use of so-called Flying Sensors (drones) to support farmers in Mozambique with their decision making in farm and crop management.
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.
Progress so far
- 14 local Flying Sensor operators have been trained and obtained their certificate.
- 10 Flying Sensors are now operational.
- Over 2,800 farmers are receiving our service, of which 71% is female.
- The number of people benefitting is over 14,000.
- ThirdEye’s service area is over 1,800 ha.
- Water productivity is increased by 55%, meaning more crop per drop.
- Additional operators will be selected and trained.
- Additional Flying Sensors will be supplied.
- The number of smallholder farmers benefitting from the ThirdEye services will be increased.
- The area where Flying Sensor information is collected will be expanded.
- Focus will be on business development to ensure long term sustainability.
- Exploring new project areas and partnerships.
- Transition to also deliver ThirdEye services to commercial farmers.
- Developing additional Flying Sensor services.
- Extra public relations activities.
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.
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.
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This project is made possible through the support of the Securing Water for Food: a Grand Challenge for Development. The partners of this program are the United States Agency for International Development (USAID), the Swedish International Development Cooperating Agency (SIDA), and the Ministry of Foreign Affairs of the Kingdom of the Netherlands. It was prepared by FutureWater and does not necessarily reflect the views of the Securing Water for Food partners. Further information about Securing Water for Food can be found at www.securingwaterforfood.org
June 2016, Thesis Report
Identifying and designing business models for innovative Flying Sensor services in Mozambique
J. van den Akker