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Understanding Agricultural Trade with Remote Sensing Data and Machine Learning
IAP and Spring
17: Political Sciences
In Song Kim
January 31, 2021
Tomoya Sasaki, email@example.com
Students joining the project will examine how the distribution of crop production affects trade policies across countries using machine learning methods. We will use satellite images to train a model to identify the geographic distribution of crop production (e.g., wheat, rice, etc). This project will involve various methodological approaches to analyze "big data" in social science research. We will work closely with each individual UROP to develop an appropriate project based on the student's substantive and methodological interests.
Good python development skills. Participation in this UROP will be done remotely; students are expected to attend a weekly Zoom meeting with other research team members.