Yin in our lab won the first place in the Student Illustrated Paper Competition in the AAG Annual Meeting (2022), organized by the Remote Sensing Specialty Group (RSSG). His poster presentation is “CropSow: a novel modeling framework to estimate field-level crop sowing date with multi-scale satellite time series”. Congratulations!!

Chishan in our lab won the second place in the Student Honors Paper Competition in the AAG Annual Meeting (2022), organized by the Remote Sensing Specialty Group (RSSG). His paper presentation is “County-level soybean yield estimation based on Bayesian-CNN incorporating phenology dynamic”. Congratulations!!

We have recently developed an innovative hybrid deep learning model that can effectively and robustly fuse the satellite imagery of various spatial and temporal resolutions. The proposed model integrates two types of network models: super-resolution convolutional neural network (SRCNN) and long short-term memory (LSTM). SRCNN can enhance the coarse images by restoring degraded spatial details, […]

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 […]