Who needs our help?
As global population grows and climate change creates an increasingly unstable environment, food markets will face greater stress. Orbital Insight Global Crop Yield predictions provide data on crop yields for regions far in advance of when they are traditionally released, enabling clients to view crop yield data from regions of the world where no data currently exists. Orbital Insight’s Agriculture product is utilized by organizations that have interests in global crop yields: responders to global food shortages, government, and organizations that trade commodities on global exchanges.
Monitoring global crop yields from space
The Orbital Insight crop yield model utilizes three different indices generated from satellite data to create the satellite variable data for the model and are designed to operate on environments with different conditions in order to create the most accurate estimate for localized agricultural output.
The indices measure either the normalized difference in vegetation, modified soil-adjusted vegetation, and green normalized difference vegetation and provide insight into both the expanse of plant growth and the health of the plants.
Deploying a five-part model
Global crop yield projections are created through a five-variable model that encompasses a range of factors relevant to crop production. The variables in the model include weather conditions, location data, satellite data, historical yield, and information on growing seasons to produce best estimates by making use of all available data. Orbital Insight monitors these conditions in real time to generate estimates for local, regional, and global crop yields.
Furthermore, Orbital Insight’s ability to detect agricultural land where no records exist allows for the most comprehensive global coverage available. See the slideshow below for more.
Corn-yield forecasting in Illinois
The top image (off color) shows areas of poor health crops (pink) in a drought year, while the lower image shows a more robust harvest of healthier corn (green)