Grand Challenges: Monitoring Second-Generation Biofuel Crops to Inform Climate Mitigation Efforts

Climate change, and how to mitigate and adapt to it, is one of the grandest challenges currently facing our society. Land use will play a critical role in climate mitigation efforts. Many socio-economic models project unprecedented biofuel crop expansion, coupled with carbon capture and sequestration, in order to achieve 2 degrees warming targets. Unlike the first-generation of biofuel crops that displaced food crops and led to increased food prices, new second-generation biofuel crops, such as switchgrass, are able to grow on marginal lands. While biofuel crops offer the potential to significantly improve our climate mitigation efforts, the large-scale land-use change involved also has the potential to negatively impact biodiversity, water cycles, and food security. 

For her University of Maryland Grand Challenges Grant funded project on “Climate Mitigation and Land-use: Detection and Monitoring of Second-Generation Biofuel Crops in the USA,” Associate Research Professor of Geographical Sciences Louise Chini is seeking to address these concerns by developing sophisticated modeling, detection, and monitoring technologies for switchgrass. 

“We are developing a methodology for detecting switchgrass cultivation using satellite data and have already made a lot of progress on this algorithm but needed to train and validate our method with direct observations of switchgrass,” said Chini.

Chini and a former graduate student recently completed a trip to gather data on the exact locations of switchgrass crops in Crawford County, PA. They spent a day in that region driving to specific locations to confirm whether the existing datasets of switchgrass cultivation are accurate. They chose Crawford County, PA because the USDA Cropland Data Layer (CDL) dataset indicated that there was a significant amount of switchgrass being grown there, so it presented an ideal candidate for a study area. 

“We were able to document over 20 different switchgrass sites and were also able to speak with local farmers about recent switchgrass farming practices,” said Chini. 

Now that this data has been collected, the next step is to incorporate the observations into the model training algorithm and use that model to detect other areas of switchgrass growth. A detection and monitoring method based on satellite data will be useful for climate mitigation decision-making because it will help determine whether these crops are replacing food crops, whether they are being grown in areas of high or low biodiversity, whether they are using significant amounts of water, etc. The new dataset that was collected will help to inform that process. 

“This field trip was a real highlight of this project so far and will provide a valuable dataset of where these potential second-generation bioenergy crops are currently being grown,” said Chini.

To Chini’s knowledge, there are no other ground-observation datasets of this kind that are able to point to specific locations where switchgrass is being grown.

As a next step, Chini and her colleagues are considering the possibility of expanding this approach to visit more sites in other states or regions. They are also considering a return visit to the same location next summer to document which land-use conversions had happened during the previous year and develop a multi-year dataset of switchgrass cultivation for that location.

For more information about this Grand Challenges project, visit: https://research.umd.edu/climate-land-use