Team Zhang at FAU
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Glades Road
Glades Road
Glades Road
Glades Road
Glades Road
33431
Glades Road
Glades Road
Glades Road
Glades Road Kh
Glades Road
Glades Road
777 Glades Rd
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Professor Zhang' team at Florida Atlantic University. CGIS Director
Caiyun Zhang
PhD Graduate Students
David Brodylo
Md Atiqur Rahman
Mizanur Rahman
FAU Researchers Map Wide Impacts of Fire-induced Permafrost Thaw in Alaska description. FAU researchers have developed a new machine learning approach to quantify fire-induced thaw settlement across the entire Tanana Flats in Alaska, which encompasses more than 3 million acres (https://iopscience.iop.org/article/10.1088/1748-9326/acabd6). This study was featured by the Department of Energy Office of Science.
Researchers Map Wide Impacts of Fire-induced Permafrost Thaw in Alaska FAU researchers have developed a new machine learning approach to quantify fire-induced thaw settlement across the entire Tanana Flats in Alaska, which encompasses more than 3 million acres.
Dr. Zhang attended GEER in Coral Springs, FL
Dr. Zhang attended AAG 2023 in Denver and elected as Chair of RSSG. Picture with former PhD student Dr. Hannah Cooper, current PhD student Mizanur Rahman, and RSSG business meeting.
In this project, we linked eddy covariance tower measured CO2 flux with Landsat measurements, water depth and air temperature to estimate CO2 seasonal patterns and dynamics at Big Cypress National Preserve (BCNP) cypress ecosystem and Everglades National Park marsh ecosystem. A paper is published in Sept 2021 by well recognized Remote Sensing of Environment:
Zhang, C., D. Brodylo, M. J. Sirianni, T. Li, X. Comas, T. Douglas, and G. Starr, 2021. Mapping CO2 Fluxes of Cypress Swamp and Marshes in the Greater Everglades Using Eddy Covariance Measurements and Landsat Data. Remote Sensing of Environment, 262, 112523, https://doi.org/10.1016/j.rse.2021.112523
(https://www.sciencedirect.com/science/article/pii/S0034425721002431).
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
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