Research Interests
Time series remote sensing, agricultural remote sensing, machine learning/deep learning, and spatiotemporal image fusion
Education
- M.S., Natural Resources and Environment (Environmental Informatics), University of Michigan, Ann Arbor
- B.S., Geographic Information Systems, Sun Yat-sen University, China
Courses Taught
- GEOG 105 - The Digital Earth (TA) - Fall 2018
- GEOG 379 - Intro to GIS Systems (TA) - Spring 2019
Recent Publications
Liu, Y., Diao, C., & Yang, Z. (2023). CropSow: An integrative remotely sensed crop modeling framework for field-level crop planting date estimation. ISPRS Journal of Photogrammetry and Remote Sensing, 202, 334-355. https://doi.org/10.1016/j.isprsjprs.2023.06.012
Yang, Z., Diao, C., & Gao, F. (2023). Towards Scalable Within-Season Crop Mapping with Phenology Normalization and Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. http://doi.org/10.1109/JSTARS.2023.3237500
Yang, Z., Diao, C., & Li, B. (2021). A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion. Remote Sensing, 13(24), 5005. https://doi.org/10.3390/rs13245005
Diao, C., Yang, Z., Gao, F., Zhang, X., & Yang, Z. (2021). Hybrid phenology matching model for robust crop phenological retrieval. ISPRS Journal of Photogrammetry and Remote Sensing, 181, 308-326. https://doi.org/10.1016/j.isprsjprs.2021.09.011