The Locust Vegetation-Impact Model estimates the impact of locusts at the district level using NDVI (normalized difference vegetation index), which measures plant greenness and is an important indicator of plant health. Gro’s model was initially developed for East Africa and expanded to other regions using similar methodology. It now covers Ethiopia, Eritrea, Kenya, Somalia, Uganda, Sudan, South Sudan, Saudi Arabia, Yemen, Iran, Pakistan, and India.
Customers use this model to
Why It Matters
Gro's model allows Gro users to gauge the amount of cropland that may be affected by locusts, which can have a significant impact on harvest sizes for a given region. If not mitigated, locust infestation can have a devastating impact on crop yield and thus affect a nation’s food security and global trade flows. Gro developed the Locust Vegetation-Impact Model in response to the 2020 locust invasion, which started in the Horn of Africa and spread as far as India and Pakistan. Gro’s Rapid Response Data Science team organized disparate data and quickly applied it to make sense of a significant emerging issue. By May, the FAO estimated that locusts threatened the food security of more than 42 million people across 10 countries. Gro worked with multiple governments to inform humanitarian relief efforts to both mitigate the risk to crops and estimate harvest losses to avoid food shortages.
Gro’s Locust Vegetation-Impact Model uses pixel-level data to assess changes in vegetative health at 250-meter (273-yard) resolution. The impact assessments are then aggregated to the district level to provide broader insights. The data is publicly available in Gro’s Locust Impact Tool Kit so humanitarian groups can better predict food shortages, deliver targeted relief, and identify areas in need of proactive pesticide application.