RTI uses cookies to offer you the best experience online. By clicking “accept” on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI uses cookies and how to manage them please view our Privacy Policy here. You can “opt out” or change your mind by visiting: http://optout.aboutads.info/. Click “accept” to agree.


How Can Remote Sensing be Used to Strengthen Food Security?

Agricultural decisionmakers in developing countries need better information to make policy and investment decisions that could have major implications for their country’s food security. For instance, which crops are growing where? What yields can be expected? What are the average plot sizes? Unfortunately, this data can be extremely expensive to collect and existing data is often outdated, error-prone, or without the right metadata to make sense of it.

Advancements in remote sensing technologies—including drones and high-resolution satellite imagery—and the advent of improved data processing and machine learning all hold promise to revolutionize the cost, resolution, and accuracy of collecting agricultural information. However, these technologies can also be difficult to apply and sustain.  RTI’s internally funded Grand Challenge project in Rwanda is applying recent advances in remote sensing to determine how insights and data from these technologies can be harnessed to promote food security in areas of need.

Continue reading this blog post for the ICT4D Conference, by RTI Senior Economic and Policy Analyst Daniel Lapidus.

Disclaimer: This piece was written by Daniel Lapidus (Senior Economist and RTI Climate Liaison) to share perspectives on a topic of interest. Expression of opinions within are those of the author or authors.