As agricultural research continues to become more entwined with technology, smart farming – a phrase that encompasses research computing tools that help farmers to better address issues like crop disease, drought and sustainability – has quickly become a ubiquitous term in Ag labs across the country.
As agricultural research continues to become more entwined with technology, smart farming – a phrase that encompasses research computing tools that help farmers to better address issues like crop disease, drought and sustainability – has quickly become a ubiquitous term in Ag labs across the country. The availability of NCSA resources like Delta for researchers, both nationally and on the University of Illinois Urbana-Champaign (U. of I.) campus, has fostered a hotbed of cutting-edge research projects in the agricultural domain.
Yi-Chia Chang, a Ph.D. student at the U. of I., focuses his research on machine learning (ML) and remote sensing. His team’s most recent research, published in arXiv and accepted to IEEE IGARSS 2025, concerns crop mapping.
Imagine you’re a farmer, and you’re planning what to grow this season. You may want to know what crop would be most valuable to grow. If you’re a policymaker, you might want to know if there’s a shortage of a particular crop to decide whether or not to incentivize farmers to grow it through subsidies. To do this, you’d have to know what’s currently growing to make those decisions – crop mapping is the tool needed to efficiently record which crops are growing and where.
Read More: University of Illinois Urbana-Champaign
Photo Credit: fietzfotos via Pixabay
