Explore global food production potential with Project Eden’s ILUM
Project Eden has launched its first product: ILUM (Interactive Land Use Map). The web application allows users to explore the food production reality and potential at a global scale. Anyone, from large agricultural producers to amateur backyard growers to the scientifically curious, can get some use out of the app.
ILUM provides visual information on the geographic distribution of production sites for 42 different crops. Using machine learning, Project Eden studied the relationship between crop output and climatic data to be able to produce potential estimates for each crop on any location on the Earth. With this, Project Eden aims to help farmers and homeowners identify food production opportunities and a possible misuse of their land. The main tool that ILUM offers to explore these opportunities is the “Interesting Points” feature, which highlights those spots on the planet where current production for a given crop is zero or unknown but Project Eden’s estimations rank it as one of the most productive points for that same crop.
An example of the “Interesting Points” feature in action is seen when querying for banana growth potential. When the team behind ILUM saw Southern Chile light up, they initially thought that their model must be wrong, as Chile is not known as a banana exporting nation. However, they were delighted to get some confirmation to their findings when they came across a 2011 report by the Government of Chile that revealed that the value of Chilean banana exports rose 1161% in that year. Eureka!
This unexpected production potential found in Chile is precisely the kind of insight that Project Eden is trying to facilitate: to call attention to areas that are not yet at their optimal growth capacity. Other examples include northern Spain and Washington State as potential locations for Cocoa growth!
The team will continue to work to improve the models and to produce more accurate predictions. A planned future release would allow users to visualize how the geographic distribution of crop production could be affected by climate change in the near and distant future.