Team Zhang at FAU

Funded by USACE, we are using multiple remote sensing datasets like hyperspectral imagery, lidar, and satellite imagery to estimate and map active layer thickness (ALT)/thaw depth and snow depth to investigate the coupling of vegetation and permafrost at permafrost experimental sites adjacent to Fairbanks, Alaska. We developed machine learning based models and calibrated the model using multiple years of field measurements. Two papers are reporting these results and findings.

Zhang, C., T. A. Douglas, and J. Anderson, 2021. Modeling and Mapping Permafrost Active Layer Thickness using Field Measurements and Remote Sensing Techniques. International Journal of Applied Earth Observations and Geoinformation, 102, 102455. https://doi.org/10.1016/j.jag.2021.102455

Douglas, T. A., and C. Zhang, 2021. Machine Learning Analyses of Remote Sensing Measurements Establish Strong Relationships between Vegetation and Snow Depth in the Boreal Forest of Interior Alaska. Environmental Research Letters, 16, 065014. https://iopscience.iop.org/article/10.1088/1748-9326/ac04d8