Yilun in our lab won the third place in the Student Honors Paper Competition in the AAG Annual Meeting (2021), organized by the Remote Sensing Specialty Group (RSSG). Her paper presentation is “Monitoring Multi-level Forest Phenology with Time Series Satellite Imagery”. Congratulations!!

We develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models, and can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois. The paper […]

Prof. Diao has been awarded a National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) Award for her project entitled “CAREER: Scalable Remote Sensing Computational Framework for Near-real-time Crop Characterization.” The CAREER Award is highly competitive and indicates a faculty member’s potential to serve as an academic role model in research and education.

We have a new USDA project, in collaboration with Dr. Shaowen Wang, to conduct intelligent field-level crop type mapping, crop phenology and condition retrieval, crop yield estimation, and forecasting at varying spatial and temporal scales. See more info: https://las.illinois.edu/news/2021-04-29/bringing-more-data-crop-forecasting  

Welcome Tianci and Yin to our lab! Tianci received her Master degree in Photogrammetry and Remote Sensing from Wuhan University, and Yin received his Master degree in Environment and Sustainability & Data Science from the University of Michigan. They joined our lab this fall, with research interests of remote sensing and machine learning in agricultural […]