Agricultural monitoring for food preparedness

Source: ESA, Earth from Space: Swedish landscape

, https://www.esa.int/ESA_Multimedia/Images/2023/02/Earth_from_Space_Swedish_landscape

Sweden’s food security depends on a stable and productive agricultural sector, but climate change is making growing conditions less predictable. Droughts, flooding, late frosts, and pest outbreaks can cause significant crop losses — and their effects often go undetected until it is too late to intervene effectively. For agencies like Jordbruksverket, which oversees agricultural policy and food supply preparedness, early detection of crop stress across large areas is a critical capability gap.

In this challenge, teams could develop methods for monitoring crop health and detecting drought, flooding, or other stress factors at an early stage. By combining multispectral satellite imagery from Sentinel-2 — which captures vegetation indices such as NDVI and leaf area indicators at 10-metre resolution — with radar data from Sentinel-1, weather observations, and agricultural reference data, participants can build solutions such as:

  • Early warning systems that flag anomalies in crop development before they become visible on the ground
  • Regional yield forecasts based on satellite-derived growth patterns combined with historical and meteorological data
  • Stress classification maps that distinguish between drought, waterlogging, nutrient deficiency, and other causes of reduced crop vigour
  • Decision-support dashboards for farmers, municipalities, and agencies responsible for food supply preparedness

Jordbruksverket is responsible for Sweden’s agricultural policy and plays a key role in national food security planning. Satellite-based crop monitoring at scale would strengthen their ability to assess production risks, coordinate support measures during adverse growing seasons, and provide data-driven input to Sweden’s broader total defence planning — where food supply resilience is a recognised priority.

The goal in this example could be to demonstrate how satellite data and AI can transform agricultural monitoring from reactive reporting into proactive, near-real-time situational awareness — supporting both everyday farming decisions and national preparedness.