This MIT feasibility project investigates the opportunities of an innovation project for determining the biomass potential from local nature management and green maintenance using the publicly available Lidar point cloud of the Netherlands.

The results of this feasibility project may lead to an innovative logistics support service where producers and consumers who play a role in the local biomass chain (e.g. nature management organizations, regional governments, energy producers) are provided advice and insight in the stock and availability of local woody biomass suitable for district heating projects or other local energy projects and biobased applications.

In the planned development path, a prototype of this service will be developed, demonstrated, tested, and validated for a pilot area. Using segmentation and classification algorithms, individual trees will be identified and tree-specific parameters relevant to biomass determination will be extracted. The economic perspective and market potential will also be investigated and relevant literature will be reviewed.

With a total annual turnover of approximately 500 million euros, the Netherlands is a major player in the production, import and export of fruits. In spring, when the night temperature drops below freezing point and fruit trees are flowering, fruit growers must protect their crops. If the flower buds were to freeze then no fruit is formed, resulting in enormous economic losses. Protecting the buds is usually done with the help of water, which requires an average of 30 m3 of water per hectare per hour. If several nights of frost occur the limit on water availability can be reached quickly. Moreover, if the quality of the water is not sufficient (e.g. due to salinity), the water can also cause damage to the crops. As a result, about 30% of the fruit companies in the Netherlands cannot use water for frost protection.

As an alternative to using water, wind machines to protect fruit trees against frost is emerging as a promising new and innovative technique. The propeller of the wind machine mixes the cold air with the higher, warmer air and can thus raise the temperature on the ground by several degrees. This feasibility project explores the opportunities of an innovation project for monitoring the effectiveness of wind machines for frost protection in fruit cultivation using flying sensors (drones) equipped with a thermal thermal imager. The results of this feasibility project may lead to an innovative information service intended for fruit growers to:

  1. Provide insight into the effectiveness of wind machines for frost protection as a cost-effective and sustainable alternative to spraying water. This service can target growers who already use wind machines and want to know how effective wind machines provide protection against night frost, but also growers who are considering wind machines and want to know to what extent the application can be suitable for their field.
  2. Advise how the application of wind machines can be optimized in the business operations of fruit companies. This includes optimal placement of the wind machine in the orchard and whether the wind machine is properly adjusted for the type of fruit being grown. This relies on what rotational speeds are needed for a given temperature increase, at what angle the propeller should be aimed, etc.)

A prototype of this service will be developed and demonstrated for a pilot area through a development process. An important part of the development trajectory is research into and development of a:

  1. State-of-art interactive visualization tool to visualize spatial information within a
  2. (beta) web application such as a dashboard to offer the innovative information service to the end user (fruit grower).

The power of flying sensors with thermal imaging cameras is that the temperature-increasing effect of wind machines can be measured very precisely and can also be mapped spatially. This visual information can provide the fruit grower with insight and confidence that wind machines are effective for frost protection.

In Sub-Saharan Africa, population growth, associated food demand and pressure on natural areas have all increased greatly. Agricultural intensification – more production from the same acreage – remains a key solution to these challenges. One of the cornerstones of intensification is that of a higher and more productive use of inputs, such as fertilizer and water. So far, the average production has remained low and a significant yield gap still exists, mainly among small scale producers (SSPs). The limiting factors are (partly) caused by weather and climatic changes but also by a lack of agronomical knowledge, proper inputs, fertilizers and (climate smart) irrigation techniques. Thanks to the digital revolution Africa is going through, many commercial farmers already have access to a wide range of agricultural services. However, such solutions are not yet accessible to SSPs due to their costs.

A consortium led by FutureWater will collaborate with ETG agronomists and the Empowering Farmers Foundation (EFF) to work together with 60 selected maize, coffee, and tea farmers from around the country to implement Climate Smart Agricultural practices, such as crop rotation to rejuvenate soil nutrients, or mulching to reduce weeds and water erosion. By using drones to monitor the application of these sustainable crop interventions from the selected farms, the project team will also be able to use the data to assess crop productivity improvements, create crop calendars to increase harvest yields, and understand land use changes to protect encroachment into biodiverse areas. Soil samples will also be collected and analyzed to identify soil nutrition deficiencies and design appropriate soil enhancement measures that will be implemented on demo farms. The success of this pilot project will provide learnings on how it can be scaled up to reach more farmers and assess its replicability across different geographic locations.

Over the past years FutureWater and HiView managed to develop a low-cost agricultural drone technology which revolutionized the applicability of geo-information services for African farmers: ThirdEye. With the flying sensor service successful local enterprises were established that provide a low-cost drone service to small- and largescale farmers, both in Mozambique and Kenya. ThirdEye’s young agronomist-drone operators support farm decisions based on the flying sensor crop mapping that is viewed on a tablet. Integrating crop nutrition advisory and other improved agronomic practices into the ThirdEye service will bring the (extension) service up to the next level. In this project, we complement the work of flying sensors by ThirdEye with the agronomic service model of Holland Greentech including input distribution, demonstrations and field days, farmer training and coaching and soil testing.

By merging agronomic advisory services making use of low-cost flying sensors, soil testing, climate smart inputs, farmer coaching and an interactive online planning & monitoring portal, the farmer is able to improve his/her:

  • Planning: What crop to grow in the season based on expected weather, crop prices and market demand;
  • Cropping: When to sow the seed based on the type of crop and predicted weather
  • Management: When and where to irrigate, fertilize and apply pesticide. This can help reduce the amount of inputs used in the farm and increase yields, thus helping with profitability.
  • Harvest: When to harvest the crop based on market prices and predicted weather.
  • Market linkage: The ability to make informed decisions on where to sell their produce, which may increase their income.
  • Climate resilience: Option to order climate smart inputs and technologies from different suppliers. These technologies include hybrid seeds, propagation units and greenhouses, (drip) irrigation equipment, soil analysis, biological soil enhancers and biological pest control products.

This project is a collaboration between ETG Kenya, Empowering Farmers Foundation, Eco-Business II Sub-Fund Development Facility, HiView, FutureWater, Holland Greentech and ThirdEye Kenya. For more information visit: https://www.ecobusiness.fund/

Geodata tools have been developing rapidly in the past years and are vastly adopted by researchers and increasingly by policy-makers. However, the is still great potential to increase the practical application of these tools in the agricultural sector, which is currently applied by a limited number of ‘pioneering’ farmers. The information that can be gained from geodata tools on irrigation management, pest and nutrient management, and crop selection, is a valuable asset for farmers. Key players for providing such information to the farmers are the extensions officers. This project aims at training extensions officers in the use of these geodata tools. The beneficiaries in Egypt are: Tamkeen for Advanced Agriculture, FAODA, IDAM, Bio-Oasis, and LEPECHA. The selected participants will receive a training programme which consists firstly of several session on the background and theory of the geodata tools, provided through our online teaching platform (futurewater.moodle.school). Starting from May (2021) field schools will be set up to use the geodata tools for decision-making in these demonstration plots. In addition, modules are taught on the quality of the data, and profitability of such tools. Altogether, a group of carefully selected participants will receive training on these innovative tools and create a bridge to providing this information to farmers specifically the smallholder farmers.

Aim of the training

The training will enhance capacity of Egerton educational staff in accessing and using innovative data and tools in the public domain, to analyse crop performance and irrigation management. During the training, university participants will be specifically supported in developing course modules based on the skills gained. To maximize the impact in addressing the need for increased quality of higher education in the agricultural sector, representatives from other institutes, ministries and private sector companies will also be invited. The training will allow the staff to gain advanced skills in working with flying sensors (drones) and satellite-derived data to support agricultural and water-related challenges, such as pests and diseases, water efficiency in agriculture to enhance food security, and drought monitoring. They will acquire insight in and knowledge on analyzing the performance of crops, making the right intervention decisions and giving irrigation advice. For public sector representatives, the training objective is to obtain skills that can be directly and sustainably implemented in their respective organizations.

Overall, the Kenyan society at large will benefit from improved food security provided by well-educated agricultural researchers and professionals. This project forms an important step in the capacity building strategy as it focuses on strengthening the universities and preparing them to provide high quality education to the future generation agronomists and agricultural managers, as well as upgrading the knowledge of current professionals.

The training costs of four stages: an online training course, followed by an in-country training program, symposium and post-training support.

Stage 1: eTraining course

The first stage involved a weekly online training course that will start in January 2021, with a total of six sessions in six weeks. Participants will be consisting of University and TVET faculty members, university students, PhD candidates, researchers, Kenya Agricultural & Livestock Research Organization (KALRO) staff members, Agriculture Extension Staff from the County Government who are already involved in agricultural research and training and other private sector partners. Staff members from the university will be those that are involved in teaching agronomy, horticulture, agriculture engineering and agriculture extension courses and programs, i.e., soil, nutrient and water management, dryland farming, irrigated agriculture and crop protection. Non-university attendants will be technical staff who are close to the decision makers within their organizations. This will enhance the impact of the training by embedding the use of flying sensor and satellite-derived data for agriculture within these organizations and make sure that Kenya will pursue its activities in making use of this kind of information.

This first stage of the training course will be online and will focus on:

  1. Real Water Savings in Agricultural Systems including potential field interventions
  2. The use of WAPOR to access remotely sensed derived data
  3. The use of flying sensors (drones) in agriculture

The course will end with a test and evaluation and graduates will receive a certificate.

Stage 2: Targeted in-country training

After the first stage training a second in-country training will take place with a smaller group, focusing on the use of drones in agriculture. Here a selected group of 12 to 18 members will be trained. Focus will be on staff with lecturing responsibilities, to ensure impact on higher education provision and transfer of the new skills to students.

The in-depth training will consist of:

  1. Operating flying sensors manually and automatic, the processing of the collected data using open source software, interpretation and the subsequent decision making (recommendations to increase productivity) for (smallholder) farmers and actors
  2. Use satellite derived (precipitation) products to run crop growth models to provide advice on when and how much to irrigate in agricultural fields

Participants will work on hands-on exercises related to crop performance analyses, water demands and crop growth modelling. Application of the new skills will be further stimulated by assigning the participants clear, tailor-made goals at the end of the second training session, to be worked on during the distant-support period.

Stage 3: Symposium/knowledge sharing

Right after the second training session, a symposium will be organized for a larger audience including the superiors/managers (who most of the times are the final decision makers) of the training participants and representatives of similar organizations. During this knowledge sharing event, trainees and trainers will actively provide contributions to showcase the newly gained skills and their added value to the respective institutions and the Kenyan agricultural sector in general. By acquainting the responsible decision makers in these organizations with the potential applications of flying sensor and satellite-derived data relevant to them, this event will be crucial in ensuring a sustainable impact of the TMT.

Stage 4: Post-training support

In this period, progress will be actively monitored and the trainers will provide post-training support to the participants. The support will be both remotely (e.g. through Skype) by the Dutch training providers but also in-person by ThirdEye Kenya staff visiting the participants for Q&A sessions and to evaluate the implementation of the skills they obtained.

The scope of the project work is as follows:

  • Train selected NCBA Clusa PROMAC staff on drone operation, imagery processing software, and crop monitoring;
  • Provide technical assistance to trained NCBA Clusa staff on drone operation, imagery processing, and interpretation of crop monitoring data;
  • Present technical reports on crop development and land productivity (i.e. crop yield) at the end of the rainy and dry season

The trainings and technical assistance for the NCBA Clusa staff are provided in collaboration with project partners HiView (The Netherlands) and ThirdEye Limitada (Central Mozambique). Technical staff of the NCBA Clusa are trained in using the Flying Sensors (drones) in making flights, processing and interpreting the vegetation status camera images. This camera makes use of the Near-Infrared wavelength to detect stressed conditions in the vegetation. Maps of the vegetation status are used in the field (with an app) to determine the causes of the stressed conditions: water shortage, nutrient shortage, pests or diseases, etc. This information provides the NCBA Clusa technical staff and extension workers with relevant spatial information to assist their work in providing tailored information to local farmers.

At the end of the growing season the flying sensor images are compiled to report on the crop development. The imagery in combination with a crop growth simulation model is used to calculate the crop yield and determine the magnitude of impact the conservation agriculture interventions have in contrast with traditional agricultural practices.

For smallholder farming systems, there is a huge potential to increase water productivity by improved (irrigated) water management, better access to inputs and agronomical knowledge and improved access to markets. An assessment of the opportunities to boost the water productivity of the various agricultural production systems in Mozambique is a fundamental precondition for informed planning and decision-making processes concerning these issues. Methodologies need to be employed that will result in an overall water productivity increase, by implementing tailored service delivery approaches, modulated into technological packages that can be easily adopted by Mozambican smallholder farmers. This will not only improve the agricultural (water) productivity and food security for the country on a macro level but will also empower and increase the livelihood of Mozambican smallholder farmers on a micro level through climate resilient production methods.

This pilot project aims at identifying, validating and implementing a full set of complementary Technological Packages (TP) in the Zambezi Valley, that can contribute to improve the overall performance of the smallholders’ farming business by increasing their productivity, that will be monitored at different scales (from field to basin). The TPs will cover a combination of improvement on water, irrigation, and agronomical management practices strengthened by improved input and market access. The goal is to design TPs that are tailored to the local context and bring the current family sector a step further in closing the currently existing yield gap. A road map will be developed to scale up the implementation of those TPs that are sustainable on the long run, and extract concrete guidance for monitoring effectiveness of interventions, supporting Dutch aid policy and national agricultural policy. The partnership consisting of Resilience BV, HUB, and FutureWater gives a broad spectrum of expertise and knowledge, giving the basis for an integrated approach in achieving improvements of water productivity.

The main role of FutureWater is monitoring water productivity in target areas using an innovative approach of Flying Sensors, a water productivity simulation model, and field observations. The flying sensors provide regular observations of the target areas, thereby giving insight in the crop conditions and stresses occurring. This information is used both for monitoring the water productivity of the selected fields and determining areas of high or low water productivity. Information on the spatial variation of water productivity can assist with the selection of technical packages to introduce and implement in the field. Flying sensors provide high resolution imagery, which is suitable for distinguishing the different fields and management practices existent in smallholder farming.

In May 2020, FutureWater launched an online portal where all flying sensor imagery from Mozambique, taken as part of the APSAN-Vale project, can be found: futurewater.eu/apsanvaleportal

The Mashhad city is the second largest city in Iran. The economic growth in the Mashhad city is strongly threatened by water shortages and unregulated groundwater extraction. The situation is critical, and the government is considering drastic infrastructural measures such as desalination and water supply from the Sea of Oman (Ministerie van Landbouw, 2018). Hence, finding cost-effective alternatives to reduce groundwater consumption in the Mashhad basin (Figure 1) is of regional interest.

The SMART-WADI project (SMART Water Decisions for Iran), carried out by a consortium of FutureWater, IHE-Delft, and local partner EWERI, focuses on farmers who irrigate their crops with groundwater. The aim is to provide up-to-date information and advice on water productivity, irrigation and farm management. The project combines the latest satellite technology for the quantification of water consumption and productivity, with high resolution flying sensor (drone) images to monitor the crop growth.

Figure 1. Mashhad basin in Iran.

Using this information in a crop model can determine the potential for improving agricultural practices and reduce groundwater consumption. This way, a higher crop yield (food production) and higher water productivity can be obtained (Figure 2). Eventually farmers receive this information in combination with recommendations regarding irrigation planning via an online portal or mobile app.

SMART-WADI is now in the phase of a feasibility project, in which the market context and technical aspects are tested. This is supported by the Partners for Water Program of RVO.nl, with co-funding from the executive project partners. Based on the first signals and the experiences of FutureWater and IHE-Delft in similar projects, it is estimated that this information service has great potential to be scaled up to other areas in Iran.

FutureWater is developing and testing a framework to predict crop yield and water productivity based on crop growth monitoring using flying sensors and remote sensing. Thanks to this innovation, farmers can timely plan field management practices (e.g. irrigation application) enhancing water productivity and reducing groundwater consumption.

Figure 2. Conceptual framework of SMART-WADI.

Twiga’ is the Swahili word for ‘giraffe’, a keen observer of the African landscape. TWIGA aims to provide actionable geo-information on weather, water, and climate in Africa through innovative combinations of new in situ sensors and satellite-based geo-data. With the foreseen new services, TWIGA expects to reach twelve million people within the four years of the project, based on sustainable business models.

Africa needs reliable geo-information to develop its human and natural resources. Sixty percent of all uncultivated arable land lies in Africa. At the same time Africa is extremely vulnerable to climate change. Unfortunately, the in situ observation networks for weather, water, and climate have been declining since the 1970s. As a result, rainfall predictions in Africa for tomorrow have the same accuracy as predictions in Europe, ten days ahead. To realize the tremendous potential of Africa while safeguarding the population against impacts of climate change, Earth observation must be enhanced and actionable geoinformation services must be developed for policy makers, businesses, and citizens. New in situ observations need to be developed that leverage the satellite information provided through GEOSS and Copernicus (Open data/information systems).

TWIGA covers the complete value chain, from sensor observation, to GEOSS data and actionable geoinformation services for the African market. The logic followed throughout is that in situ observation, combined with satellite observations and mathematical models, will result in products consisting of maps and time series of basic variables, such as atmospheric water vapour, soil moisture, or crop stage. These products are either produced within TWIGA, or are already available with the GEOSS and Copernicus information systems. These products of basic variables are then combined and processed to derive actionable geo-information, such as flash flood warnings, sowing dates, or infra-structural maintenance scheduling.

The TWIGA consortium comprises seven research organisations, nine SMEs and two government organisations. In addition it uses a network of 500 ground weather stations in Africa, providing ready-to-use technical infrastructure.

FutureWater’s main role in TWIGA is centered around the use of flying sensors to map crop conditons, flood extent, and energy fluxes, complementing and improving data from in situ sensors and satellites. Furthermore, FutureWater is involved in innovative app development.

Nowadays, projects that invest in sustainable water management and agriculture require evidence that the targeted measures to boost water productivity are effective. Water productivity monitoring therefore becomes increasingly important. Water productivity requires data on yields and water consumption (evapotranspiration). Yield data are often difficult to obtain from farmers, especially in areas with many smallholders. Evapotranspiration is even more difficult to assess in the field. Remote sensing-based and model-based monitoring of water productivity has a large potential, also to identify yield gaps and assess the local feasible effectiveness of measures.

The objective of this pilot study was to achieve plot-level maps of water productivity and yield to test a methodology to assess the performance of different farmers in order to provide them with recommendations to improve water productivity. More specifically, this pilot study combined high-resolution imagery from Flying Sensors (FS) with a crop water productivity model to assess yield and water productivity for several plots with maize in Mozambique. Canopy cover was derived from the imagery and linked with the crop model simulations to obtain water productivity maps covering the entire growth cycle. The methodology is also used for the monitoring of crop performance during the growth season and can be used to forecast yield by the end of the season.

This feasibility study demonstrated that there is an opportunity to further develop a service that monitors water productivity based on FS-imagery and crop modelling. Service costs outweigh the additional revenues obtained by farmers. The experimental development has demonstrated that the service is technically feasible and can provide the tangible outputs needed. To bring the proposed service to a higher level of maturity, it is recommended to focus future development activities on (i) Testing for different locations and crops, (ii) Further enhancing link between FS-based imagery and crop modelling, and (iii) Involving end-users and testing within a project where WP-measures are implemented.