GCRI · Fields across the Consortium
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Food and agriculture
Food system risk is the chance that production shocks, trade restrictions, input prices and household incomes combine so people cannot obtain enough safe, nutritious food. It can happen even when global supply looks adequate.
Food and agriculture in six parts.
The field, seen three ways.
Financial understanding
No platform yet in this field.
Growing conditions worldwide.
Crop greenness, root-zone soil moisture, plant growth and true-colour imagery across the world, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Growing conditions, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Growing conditions, framed on World. Layers as NASA publishes them, each with its own date.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA HLS S30Sources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (13 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
- Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 Oct 2026
- Gross primary production, 8-day total: MODIS Aqua GPP (MYD17), NASA LP DAAC · 30 Sep 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
Synchronous failure and the price channel.
The global food system concentrates production of staple grains in a few breadbaskets and export in a few corridors. A concurrent harvest shortfall, an export restriction or a fertilizer price spike can travel to import-dependent countries faster than domestic policy can respond. Access, not availability, is where acute food insecurity is decided: price transmission into local markets, household purchasing power and social protection.
- Breadbasket synchrony: climate modes such as El Nino-Southern Oscillation correlate yields across regions.
- Chokepoints: a small number of straits and ports carry a large share of grain trade.
- Input dependence: nitrogen fertilizer production is tied to natural gas prices.
- Policy contagion: one country's export restriction raises the incentive for others to follow.
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30 % of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.98 % of a year's output
- Total over direct (multiplier)
- 1.94 times
- Most affected other sector
- Energy
- Its peak inoperability
- 5.7 %
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Farming | 34.15 | 22.0 |
| Fertiliser and inputs | 0.10 | 9.0 |
| Food processing | 2.40 | 10.2 |
| Transport | 0.50 | 16.4 |
| Wholesale and retail | 0.30 | 22.6 |
| Energy | 5.67 | 19.8 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualizing uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs at GCRI: Nexus Labs
- Built in Foundry at GCRI: Nexus Foundry
- Tested at Universe at GCRI: Nexus Universe technical office
- Codified in Food and agriculture risk standards on Nexus Standards
- Published in Reports at GCRI: Publish
- Taught in Food systems and agriculture on Risk Academy
How food insecurity is measured and governed.
| Framework or body | What it governs or supplies |
|---|---|
| Integrated Food Security Phase Classification (IPC) | Five-phase severity scale for acute and chronic food insecurity, with consensus analysis |
| FAO food balance sheets and FAOSTAT | Production, trade and utilization by commodity and country |
| AMIS (G20 market information system) | Market transparency on wheat, maize, rice and soybeans |
| GEOGLAM Crop Monitor | Satellite-informed crop condition assessments |
| Committee on World Food Security | Voluntary guidelines including those on the right to food and on tenure |
Model food and agriculture as a system. Run the cascade.
Assembled from the Nexus Standards area profile Food and agriculture risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification.
Hazards
- Ice-jam flood
Systems and couplings
- Food and agriculture risk standards
- Water risk standards Common driver
- Supply chain and trade risk Cascade
- Conflict and security risk standards Feedback
- Biological hazard standards Cascade
Controls
NS-0Constitution and principlesNS-1The UNI and the artifact catalog (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)NRS-H81Hazard family: Malnutrition and micronutrient deficiency (NHS-1 health.nutrition)NRS-H43Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)NRS-N3Food and agriculture risk and resilienceNRS-C7Early warning, triggers and anticipatory actionNRS-H44Hazard family: Plant disease and pests (NHS-1 health.plant-health)
Observation
- IPC acute food insecurity analyses (listed for reference)
- FEWS NET outlooks and data (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- FAO GIEWS Food Price Monitoring and Analysis tool (listed for reference)
- ESA WorldCover 10 m land cover (listed for reference)
- Prevalence of undernourishment
- Prevalence of moderate or severe food insecurity (FIES)
- Indicator of food price anomalies
- Direct agricultural loss attributed to disasters
Example geography
- The Ganges and Brahmaputra Basin: 178 H3 hexagons at resolution 3
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
The links that make food a systemic field.
- Water: irrigated land produces a large share of global food output from a smaller share of cropland.
- Energy: fertilizer, diesel and cold chains price energy into food.
- Trade: corridors, export policy and freight rates set import bills.
- Health: undernutrition raises disease burden, and animal disease affects protein supply.
The science sits on Food Nexus; methods start from agricultural science.
The nexus signature of food and agriculture.
The sectors food and agriculture touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Food and its partners
Food gives nutrition to health (0.7), land conversion to biodiversity (0.6) and withdrawals and runoff to water (0.3).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
The methods behind the field.
- Agricultural, soil and food science
- Ecology and biodiversity science
- Earth observation and remote sensing
- Spatial statistics and geostatistics
- Forecasting and time-series analysis
- Optimization and operations research
- Econometrics
- Hydrology and water science
- Biotechnology platforms
- Water and environmental engineering
- Molecular and life sciences
- Epidemiology and public health science
- Probability and statistics
- Process and industrial safety engineering
- Climate and atmospheric science
- Policy, institutional and decision science
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why does GCRI host field gateways?
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The same subject across the Consortium.
- GRFglobalriskforum.comAgricultural, soil and food science for climate and nature governanceMandates, commitments and accountability
- GRAglobalriskalliance.comAgricultural science for development financeExposure, loss and capital
- Nexus Standardsnexustandards.comFood and agriculture risk standardsStandards that apply
- Risk Academyrisksacademy.comFood systems and agricultureWhere it is taught
- Nexus Reportstherisk.globalFood Nexus in Nexus ReportsWhere it is reported
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