Yilun in our lab has been awarded a Future Investigators in NASA Earth and Space Science and Technology (FINESST) fellowship for her project “Evaluating the Influence of Biocontrol Program on the Colorado River Biodiversity with Multi-Source Time Series Imagery.” Congratulations!!

We have systematically assessed near-surface PhenoCams and high-resolution PlanetScope time series in reconciling sensor- and ground-based crop phenological characterizations. With two critical crop stages (i.e., crop emergence and maturity stages) as an example, we retrieved diverse phenological characteristics from both PhenoCam and PlanetScope imagery for a range of agricultural sites across the United States. The […]

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, […]