Data Analytics Can Help Feed Planet

Irfan Khan

Millions of people living today in the Horn of East Africa are currently at risk from a devastating drought. Tens of thousands of refugees have already migrated to other parts of the region. While the ongoing military conflict complicates the problem, it’s the unrelenting drought that is the primary cause of the famine there. It’s a tragedy that tugs at the heart.

Although big data analytics cannot make it rain, it can be used to predict where devastating droughts might occur. Information derived from satellite imagery can give international and regional leaders as well as humanitarian groups advanced notice about where famine is a potential problem so they can prepare accordingly. As NASA points out, “Earth observations can contribute to policy makers’ understanding of hazards over years, seasons and months, giving them the ability to anticipate and plan for potential famines.”

In addition to preparing an area for the consequences of drought, analysis of satellite image data can be used in all agricultural regions to help implement sustainable farming practices. In Spain, for example, scientists are using such data to improve irrigation efficiency on farms, which is critical in a nation where 85% of the country’s water is consumed by agriculture.

Image data from space is also used to analyze the state of vegetation and soil conditions in a region. This can help farmers better predict what crops to plant and where. The problem, of course, is communicating that information in time for local farmers to make decisions about what to plant and when.

While I am truly heartbroken by the famine experienced by so many in Africa today, I am hopeful that improved imaging systems and advanced analytics models will be able to mitigate problems like drought in coming years. We need to dramatically improve food production in many parts of the globe. A major step to do so will be feeding more data into analytics systems and deliver the results to local farmers to make them more productive.