Satellite Solutions for Food Security

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Global food security faces a number of pressures, including conflict, climate change, pollution and overexploitation. North and Central Asia is a region at risk, with human activity contributing to significant levels of desertification in drylands and other fragile biomes.  Agriculture is a major source of employment in the region, accounting for more than 40 per cent of the working population in Tajikistan, more than 30 per cent in Azerbaijan and Georgia and more than 20 per cent in Armenia, Turkmenistan and Uzbekistan. Agriculture underpins the livelihoods of rural populations, which are often among the poorest sectors of society. 

With greater efficiency and optimization, the agricultural sector can save water and resources, increase yields and adapt to new climatic realities. That kind of innovation is the theme of this year’s World Food Day (16 October) “Innovate today. Nourish tomorrow.” Across North and Central Asia, geospatial technology is already helping both farmers and policymakers. Making the most of it, however, depends as much on skills and on institutions working together as on the technology itself.

Geospatial technology can support farmers in decision-making processes through online platforms and applications. In Kazakhstan, the application AgroData integrates data from 226 agrometeorological stations, giving farmers real-time information on weather, soil moisture and crop health. Farmer App in Azerbaijan and KosmosAgro in the Russian Federation offer similar tools, from monitoring vegetation growth to estimating yields and spotting pests. 

Kyrgyzstan has partnered with the World Food Programme in a project that equipped around 5,000 rural community members and farmers to interpret and apply climate information from new portable equipment deployed across 13 sites. Kyrgyzstan is also building AgroMap, a free application for farmers which will provide real-time information on environmental and agronomic conditions

Satellite technology can also help guide policy at the local and national levels. In Turkmenistan, geographic information system technology has been employed around Lake Altyn Asyr to identify suitable areas for agriculture. In Kazakhstan, the AgroSpace platform provides geospatial data on agricultural land to justify subsidy applications by the mapping and verification of field borders, crop history and current crop conditions.

Putting these tools to work also depends on skills. In 2024, ESCAP – with funding from the Russian Federation – launched a project to strengthen the capacity of Central Asian countries to use Earth observation (EO) and geospatial technologies for monitoring agricultural conditions and the impacts of drought. By July 2026, its training activities had engaged over 140 technical staff and experts from space agencies, hydrometeorological services, research institutions and universities.

The project, which spans Kyrgyzstan, Tajikistan and Uzbekistan, draws on technical support from Regional Drought Mechanism service nodes in China, India and the Russian Federation. It has also supported countries in operationalizing national drought monitoring systems, including the demonstration of a prototype national portal, led by Uzbekspace, for accessing, visualizing and analysing EO-derived drought and crop information. Cloud-based EO platforms have also helped address digital infrastructure and connectivity constraints in Kyrgyzstan and Tajikistan.

Institutions matter too. For satellite data to consistently guide food and agriculture policy, it needs to find its way into official statistics. That depends on two sets of institutions that have not always worked together. National statistical offices hold census and survey data and the mandate to produce and publish official figures; geospatial and cadastral agencies hold the maps, imagery and land records that tie those figures to a place. The Global Statistical Geospatial Framework (GSGF), developed jointly by the global statistical and geospatial communities, sets out how the two can be linked.

Uzbekistan is putting the GSGF into practice. Alongside its first population and agricultural census since independence, the National Statistics Committee of the Republic of Uzbekistan is using satellite imagery for land-cover mapping, starting with the Tashkent region. The approach combines satellite imagery and machine learning with cadastral parcel boundaries, so that land cover and cropland can be measured field-by-field rather than pixel-by-pixel. This matters where farmland is divided into many small plots and fields are often cropped twice a year. Field validation will check the model’s accuracy. The aim is to apply the method nationally and lay the groundwork for estimating crop area and production.

Neighbouring Kyrgyzstan shows where such collaboration can lead. With support from ESCAP’s project on Big Data for Official Statistics, the National Statistical Committee of the Kyrgyz Republic and Kyrgyzgiprozem, the national land management institute, geocoded the 2022 population census and used geospatial data to produce SDG indicators on rural road access and land consumption, which informed the country’s 2025 Voluntary National Review. The Committee has since adopted a national roadmap to extend the approach to further indicators.

As extreme weather events become more frequent and as slow-onset environmental crises unfold, the need for adaptation and resource management is clear, and geospatial innovation, backed by the right skills and institutions, can help meet it. The challenges North and Central Asia face are representative of those faced by the world, and its successes can serve as inspiration to us all. Many of the examples above feature in ESCAP’s forthcoming Geospatial Practices for Sustainable Development in North and Central Asia 2026: A Compendium, which showcases 100 practices from across the subregion.  

The authors are Kareff May Rafisura, Chief of the Disaster Risk Reduction Section, ESCAP; Richard Pearce Tonkin, Statistician, ESCAP and Ladislav Charouz, Former Contractor, ICT and Disaster Risk Reduction Division. 

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