Rice Phenology Estimation and Enabling Yield Boosting using Remote Sensing and Drone Imagery
Rice is one of the most important food sources with more than 3 billion people depending on it for 20% of their calories. With the decreasing resources in the world and a fierce competition in global trade, maximizing yield is of utmost importance. For this, rice phenology must be studied, traditional methods of rice phenology estimation are ineffective and do not scale well. This project collected a novel UAV dataset of multiple rice variants in South Punjab, and estimated the rice yield to ensure farmers obtain a cost-effective rice produce. The scope of this project is aimed at revolutionizing rice production by providing accurate and timely phenology predictions, enabling farmers to optimize their farming practices, increase crop yields, and contribute to sustainable agriculture. The integration of remote sensing, drone imagery, and advanced data analysis techniques, along with the development of a user-friendly web application, will empower stakeholders and drive positive change in the rice farming industry.
Demo VIdeo
Faculty
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Dr. Zuhair ZafarDr. Zuhair Zafar
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Dr. Muhammad Moazam FrazDr. Muhammad Moazam Fraz
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Dr. Muhammad ShahzadDr. Muhammad Shahzad
Students
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Muhammad Qasim Khan (BSCS-9)
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Dawood Wasif (BSCS-9)
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Malik Zeeshan Ahmad (BSCS-9)