Crop Monitoring and Yield Modeling Using Drone Technologies in Ghana at International Fertilizer Development (IFDC)

Methodology

• This student would analyze the influence of climate, soil, and remotely sensed variables on crop yield using advanced statistical methods and then visualize the variability of yields as influenced by the variables using predictive mapping. The study area would be FERARI field trial locations and the student shall be required to produce a clear methodology for achieving the objectives. In the course of the internship, the student would receive assistance and supervision from the FERARI team.

Output

• At the end of the research, the student shall produce a report to FERARI on this research and extract the most important findings in a policy brief. The student would also be assisted to produce a research article that can be published in a scientific journal for our wider international audience.

Qualification

• An MPhil/MSc student in agronomy, Agro-geomatics, Fertilizer Science and Technology, or related studies. Applicant must have completed his/her course work and be ready to start the research component. The applicant must demonstrate high analytical capabilities, knowledge in remote sensing and UAV, be creative, pragmatic, and flexible in finding solutions to the problem. Preferably, the applicant should be knowledgeable in regression, geostatistics, machine learning, and software packages such as R, Pix4D, QGIS, and Microsoft Excel.