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Earth Observation for Food Security

Earth observation can contribute to both, providing a short-term humanitarian response to food crises and supporting the establishment of longer-term development cooperation to improve food security and increase the sustainability of food systems.

Overview: why it matters?

According to the Global Report on Food Crises of 2021, a joint publication by a network of 15 partners and facilitated by the Food Security Information Network (FSIN), 155 million people in the 55 countries selected for the report experienced acute food insecurity of a severity corresponding to IPC/CH Crisis or worse[1]  in 2020. This number has increased by 20 million compared to 2019, with 63% of those experiencing food insecurity located in Africa. Another 208 million were classified as IPC/CH Stressed, at the cusp of acute hunger and at risk of crisis. While conflict is the main driver of food insecurity for 99 million people in 23 countries, other key drivers include economic shocks, which have been exacerbated by the COVID-19 global pandemic and climate change causing extreme weather events which have affected 15.7 million people. As regards chronic food insecurity, data from the 2020 State of Food Security and Nutrition in the World (SOFI) showed that 2 billion people in 2019 did not have access to safe, nutritious and sufficient food, of which 750 million were exposed to severe levels of food insecurity. The SOFI 2021, which is expected to be published in July 2021, will provide a further assessment of how the above-mentioned situation has been further impacted by the COVID-19 global pandemic.

Considering the impact and consequences weather events, conflict and economic shocks can have on food security, it is important to set international frameworks and response mechanisms to address these challenges. Earth observation (EO) can contribute to both, providing a short-term humanitarian response to food crises and supporting the establishment of longer-term development cooperation to improve food security and increase the sustainability of food systems.

EO, in particular, remote sensing and meteorological data, can support the development of early warning systems for the prevention of food crises and to inform rural development. This data can be used to effectively detect, monitor, and prevent food production disruptions, thus ensuring a contribution to increasing the resilience to food crises in affected countries. Moreover, EO can inform natural resources management contributing to longer term development, the protection of biodiversity and food systems sustainability that reduce the risk of food insecurity. Possible applications in this case include digital services to agriculture as aiming at improved efficiency of farming inputs and the use of EO data for agricultural management and planning. New technologies and applications that will be presented in this brief will increase the potential for the use of EO-derived products in both contexts.

eo_for_food_security_value_chain

 

The UN and Food Security

The United Nations and the European Commission are two of the main actors shaping the food security policy framework. Already in 1996, UN member states pledged their “political will to achieving food security for all” in what is known as the Rome Declaration on World Food Security. In general, the UN with specialized agencies such as the Food and Agriculture Organization (FAO) and the World Food Programme (WFP) is the main actor measuring and monitoring food insecurity globally. It does so by producing reports such as the SOFI and by contributing to multi-stakeholder assessments such as the Global Report on Food Crises. UN agencies also develop information tools as for example the World HungerMap, allowing to track hunger in real-time. In 2015, Sustainable Development Goal 2 reaffirmed the commitment to end all forms of hunger and malnutrition by 2030, making sure all people, especially children and the most vulnerable, have access to sufficient and nutritious food all year round. Key priorities identified under SDG 2 are to end hunger and provide humanitarian food assistance, to ensure food security and enhance resilience to food crises, but also to promote sustainable agriculture and innovation. Food security is identified as a fundamental priority also in the Paris Agreement, taking into consideration the adverse impact of climate change on food production.

 

The EU and Food Security

The EU approach to reaching SGD 2 is built upon four main pillars:

  1. Enhancing the resilience of the most vulnerable to food crises,
  2. Fighting malnutrition and helping secure nutritional health and well-being for present and future generations,
  3. Supporting responsible investments in agriculture and food systems,
  4. Promoting innovation for sustainable agriculture and food systems.

In particular, the work of the department for European Civil Protection and Humanitarian Aid Operations (DG ECHO) coordinates short-term humanitarian response in the case of food crises, while the department for International Partnerships (DG INTPA) plays a pivotal role in the implementation of the EU evidence-based approach to development assistance and international cooperation aimed at fostering resilience to food crises, agricultural development and the longer-term sustainability of agri-food systems relying on the protection of biodiversity.

EU action in the field of food crises is guided by key policy documents such as the EU Communication on Humanitarian Action, which proposes a series of steps to expedite humanitarian aid provision including for food resources in situation of crises. Regarding food insecurity, the EU Consensus on Development  embraces the SDGs, the comprehensive Strategy with Africa calls for a joint effort to address the challenges of food security in Africa and the Farm to Fork Strategy, which is at the heart of the Green Deal, mentions the EU plan to set up a food crisis response mechanism coordinated by the Commission and involving Member States. The Common Agricultural Policy outlines the EU role in ensuring global food security and in supporting farmers and the EU agricultural sector. Lastly, as highlighted in the EU Biodiversity Strategy, biodiversity loss also threatens food systems, putting food security at risk and for this reason, the protection and restoration of biodiversity are vital to ensure food security.

 

The Knowledge Centre on Food Security and Nutrition is a one-stop source of curated Knowledge on 11 topics related to Food and Nutrition Security and Sustainable Food Systems. This science-policy interface works on three different streams:

  1. Knowledge management:
    1. Organize and make accessible data, information and tools
    2. Analyze, synthetize, and develop evidence
  2. Communities’ development:
    1. Facilitating networking of experts, researchers, policymakers
  3. Development of new knowledge:
    1. Identify research needs and gap
    2. Conduct collaborative research.

 

Current Use of EO for Food Security

Given the EU evidence-based approach to humanitarian and development assistance, EO data and derived products can provide a sound knowledge base for the implementation of effective food security policies. Low spatial resolution satellite-based vegetation health indicators have been widely used for agricultural monitoring and drought detection since the early days of EO, while more recently, improved resolution data from the Sentinel 2 mission has dramatically increased the capabilities for agricultural monitoring and crop management worldwide. Sentinel 2 imagery cover the surface of the Earth every 5 days at a resolution of 10 meters and make available 4 Terabytes of new data per day, meaning they also need adequate computer resources for processing and analysis.

EO-derived products for food security are made accessible in two main ways that are presented below to a number of actors including DG ECHO, DG INTPA and EU delegations in countries affected by food crises, food security analysts, international organisations and the general public, including small farmers.  

  • Agricultural Monitoring Systems provide near real time information on crop conditions and yield forecasts at different geographic scales. In Europe for example, the JRC MARS Bulletin provides monthly crop monitoring reports and yield forecasts for the main crops for the EU Member States and neighbouring regions throughout the growing season. At the global scale, EO based platforms such as the Anomaly Hotspots of Agricultural Production (ASAP) produced by the JRC or the Agriculture Stress Index System (ASIS) produced by FAO make available qualitative crop conditions information which is an important input for detecting anomalies in food production and inform humanitarian and food security policies about upcoming shocks on food supply, possibly leading to food crises, and allowing early response planning. Crop monitoring systems developed by international agencies and country governments also contribute to multi-stakeholder crop monitoring systems such as the Crop Monitor for Early Warning (CM4EW) managed by the G20 initiative GEOGLAM.
  • Support to food security assessments: EO products and early warning systems also provide additional and frequently updated indirect evidence to the Integrated Food Security Phase Classification (IPC) and the Cadre Harmonisé (CH), the reference food security analysis protocols used by the Global Report on Food Crises. EO products are particularly critical in hard-to-reach areas where no other data can be collected. The JRC is supporting the joint efforts of all partners of the CH Earth observation task force that routinely provides EO-derived evidence to inform the food security situation in those inaccessible areas. Those EO products are related to agriculture but also to biomass status, water availability, flooding, land abandonment and potentially also to population movements and infrastructure destruction. The Copernicus Emergency Management Service (CEMS) rapid mapping services, which use mainly Very High-Resolution Imagery for detailed mapping of damage to infrastructure and crops provides useful post disaster assessment for extreme events with possible major impacts on food security including earthquakes, floods, conflicts.

    Both the agricultural monitoring systems and the support to food security assessment activities require reference and auxiliary data, which in some cases are also based on EO, as well as tools and computing resources for their production. Cloud computing platforms for example play an increasingly important role for running algorithms on EO data that produce outputs relevant for food security.
    The COPERNICUS DIAS provide such kind of capacity, and specific cloud computing technologies in the food security domain, building on the use of Sentinel 1 and 2 satellite data, which has been explored by the DIAS precursor project, the Food Security TEP. Climate data that complement vegetation and earth surface observation data are provided for example by the C3S platform, which has also developed climate services in support of agriculture and food security with the Global Agriculture Sectoral Information System. Finally, agricultural monitoring and food security assessments require reference data such as for example thematic maps showing the location of different crop types. Recent projects that are helping to make such maps available at the country level are the Sen2Agri project  or the Copernicus4GEOGLAM component of the Global Land Service, which aims to strengthen national and sub-national level agricultural monitoring systems in GEOGLAM partner countries. Capacity building in developing countries for the use of latest space technology for food security has been a priority for the European Commission for many years, for example with the Monitoring of Environment and Security in Africa (MESA) project and under the COPERNICUS program thanks to the Global Monitoring for Environment and Security (GMES).

 

Operational Agricultural Monitoring and Early Warning Systems for Food Security

At present, there are eight regional and global scale agricultural monitoring systems providing key information for evidence-based decision-making in the field of food security. These systems cover different areas and regions of the globe, have different roles, deliver different products and are aimed at different customers. A summary of these features can be found in the table below. The FAO Global Information and Early Warning System (GIEWS) is an integrated system monitoring food availability and access globally, which has developed (in collaboration with the JRC) its own EO based agricultural monitoring system called ASIS (Agricultural Stress Index System). The USAID Famine Early Warning Systems Network (FEWS NET) publishes monthly reports on 36 of the world’s most food insecure countries and provides alerts on emerging crises in such countries, informing in the first place US food security and humanitarian policies, but also publicly available. The system includes EO based information like vegetation indicators and rainfall estimates coming mainly from sources in the US. The Chinese Academy of Science CropWatch provides data on both global and national crop production and conditions informing the Chinese government, but also made publicly available. The JRC developed the MARS Crop Yield Forecasting System (MCYFS), which provides operational estimates of area, yield and production at pan-European level for EU member states and the ASAP, which provides a monthly assessment of 80 countries with high risk of food insecurity to inform directly EC food security and humanitarian policy. The WFP Seasonal Monitor provide global crop conditions and production estimates and the latter also provides early warning of conditions detrimental to crop and pasture, which are at the basis of WFP response to food assistance.

The systems above use EO data to a different degree and with different methodologies which are generally complementary (e.g. different data sources, spatial resolutions) and aim at addressing the specific information needs of the main customers. For example, the MARS bulletin has been created to provide crop monitoring and official EU yield forecasts to DG AGRI and to EUROSTAT, while the WFP VAM service addresses the specific need of planning food assistance interventions. 

The GEOGLAM initiative launched by the 2011 G7 summit, aims at creating a multi-stakeholder product, which is based on contributions by the systems mentioned previously and national partners and provides two main global products based on monthly coordination workshops involving all sources, the Crop Monitor for AMIS focused on the global production of wheat, maize, soy and rice in G20 countries plus 7 and the Crop Monitor for Early Warning (CM4EW), which covers countries most at risk of food insecurity.

characteristics_of_the_different_agricultural_monitoring_systems

 

The JRC Anomaly hot Spots of Agricultural Production platform

ASAP was firstly developed by the JRC in 2017, starting from the experience gathered in Europe through the MARS MCYFS and it focuses on providing constantly updated information on weather and biomass anomaly that represent a risk to agricultural production and food availability in 80 countries considered at risk of food insecurity or where the EU contributes to rural development. The added value of the system is to capitalize on the latest generation of multi-scale satellite information and to make automatic agricultural drought warnings available to a team of agricultural analysts who provide monthly narratives about agricultural hotspots in countries with high risk of food insecurity. This combination of an automatic EO and climate indicator anomaly analysis with a review by agricultural analysts makes it possible to provide reliable information that is more useful, better targeted and more trustable than simple anomalies of biophysical indicators observed by satellites, which are affected by noise and are generally only proxies of agricultural production. For example, the Normalized Difference Vegetation Index (NDVI), one of the most commonly used vegetation health indicators, is useful to detect agricultural drought but is also influenced by clouds, land use changes and satellite sensor degradation. Similarly, rainfall variations can have different effects on crops depending on their intensity, geographic extent and length. This means that providing reliable agricultural hotspots and early warning information, satellite signal analysis needs to be combined with expert knowledge. Crop growth modelling and quantitative yield forecasting can only be applied in areas where there is sufficient field data and high-quality agricultural statistics for calibration and validation.

The JRC has recently introduced a new machine learning workflow for the analysis of this data and also develops customised versions of the ASAP to address the needs of users at the regional level and support capacity building. An example of this approach is represented by the East Africa Agriculture Warning Explorer, providing automatic ten days drought conditions warnings for crops and rangelands at the provincial level and developed in collaboration with ICPAC as part of the CLIMSA project.

The illustration below shows from ASAP an example of multi-scale information with automatic agricultural drought conditions warnings at province level (left side) and detailed vegetation anomaly maps at the field level (right side).

ASAP

 

Potential Use of EO and Future Developments

Looking at the potential for increased use of EO for food security, the increased availability of high spatio-temporal resolution data from Sentinel 2 made available by ESA every 5 days, and with a resolution of 10-20m, represents a big step forward for agricultural monitoring and management. Both Sentinel 1 and Sentinel 2, with their large and systematic free access imaging capacity and the spectral richness of the images, also increase the reliability and accuracy of the services offered by Copernicus for precision agriculture and open the way for the development of new services for farmers in development countries.  The opportunities offered by the COPERNICUS driven data revolution rely also on the increasing accessibility of cloud computing. Finally, innovative methods including machine learning and Artificial Intelligence applied to agricultural monitoring systems, allow to increase their automation and accuracy. A good example is the recent ASAP-Special Focus on Algeria of May 2021, which used machine-learning algorithms to automatically process and test different combinations of agro-climatic indicators for the production of quantitative yield forecasts for Algeria’s main winter cereals at the province level.

Key to increasing the use of EO in the agricultural sector will also be the development of partnerships and implementation of capacity building activities in developing countries, as well as the development of services which support the digitalization of the agricultural sector and reach small scale farmers. In this sense it will be key, not only to continue the development of services aiming at improved efficiency of agricultural inputs and machinery (e.g. precision farming applications) but also to respond to typical small scale farmers needs such as the support to land registration or tailored applications for sustainable agriculture, agro-forestry and agro-ecology. Overall, there will be an increasing need for information for monitoring agriculture related sustainability aspects, with a view to integrating governance and management across water, energy, food and ecosystems (WEFE) and to protecting biodiversity.

 

value_chain

 

Further Readings

 


[1] This terminology is based on internationally recognized standard levels of the severity of acute food insecurity as defined by the integrated food security Phase Classification (IPC Global Partners. 2019. Integrated Food Security Phase Classification Technical Manual Version 3.0. Evidence and Standards for Better Food Security and Nutrition Decisions. Rome.) and the Cadre Harmonise (CILSS and CH Partners, Manual Version 2.0 Identification and analysis of areas at risk and populations affected by food and nutrition Insecurity) [go back]