Dr. Caiyun Zhang
Professor
Phone: 561-297-2648 |
About:
Research Interests:
Hyperspectral and Lidar Remote Sensing |
Teaching
GIS 6127C: Hyperspectral Remote Sensing
GIS 6032C: LiDAR Remote Sensing
GIS 4021C/GEO 6938: Photogrammetry and Aerial Photography Interpretation
GIS 4037C/GIS 5033C: Digital Image Analysis
Book
Zhang, C ., 2020. Multi-sensor System Applications in the Everglades Ecosystem. CRC Press/Taylor and Francis Group, ISBN:1498711774; ISBN-13: 9781498711777; 334 pages.
Recent Publication
- Zhang, C., T. A. Douglas, D. Brodylo, L. V. Bosche, and M. Torre Jorgenson, 2024. Combining a Climate-Permafrost Model with Fine Resolution Remote Sensor Products to Quantify Active-Layer Thickness at Local Scales. Environmental Research Letters, https://doi.org/10.1088/1748-9326/ad31dc .
- Zhang, C., T. A. Douglas, D. Brodylo, M. T. Jorgenson, 2023. Linking Repeat Lidar with Landsat Products for Large Scale Quantification of Fire-induced Permafrost Thaw Settlement in Interior Alaska. Environmental Research Letters, 18, 015003.
- Zhang, C., D. Brodylo, M. Rahman, M. A. Rahman, T. A. Douglas, and X. Comas, 2022. Using an Object-based Machine Learning Ensemble Approach to Upscale Evapotranspiration Measured from Eddy Covariance Towers in a Subtropical Wetland. Science of The Total Environment, 831, 154969.
- 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 (open access)
- Douglas, T. A., and 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.
- 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.
- Zhang, C., X. Comas, and D. Brodylo, 2020. A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland. Journal of Geophysical Research: Biogeosciences, 125, e2020JG006002, https://doi.org/10.1029/2020JG006002.
- Zhang, C., H. Su, T. Li, W. Liu, D. Mitsova, S. Nagarajan, R. Teegavarapu, Z. Xie, F. Bloetscher, and Y. Yong, 2020. Modeling and Mapping High Water Table for a Coastal Region in Florida Using Lidar DEM Data. Groundwater, https://doi.org/10.1111/gwat.13041.
- Durgan, S*., C. Zhang, A. Duecaster, F. Fourney, and H. Su, 2020. Unmanned Aircraft System Photogrammetry for Mapping Diverse Vegetation Species in a Heterogeneous Coastal Wetland. Wetlands, https://doi.org/10.1007/s13157-020-01373-7.
- Durgan, S*., C. Zhang, and A. Duecaster, 2020. Evaluation and Enhancement of Unmanned Aircraft System Photogrammetric Data Quality for Coastal Wetlands. GIScience & Remote Sensing, https://doi.org/10.1080/15481603.2020.1819720.
- Zhang, C., 2019. Combining Ikonos and Bathymetric LiDAR Data to Improve Reef Habitat Mapping in the Florida Keys. Papers in Applied Geography, 5, 256-271.
- Zhang, C., S. Durgan, and D. Lagomasino, 2019. Modeling Risk of Mangroves to Tropical Cyclones: A Case Study of Hurricane Irma. Estuarine, Coastal, and Shelf Science, 224, 108-116.
- Zhang, C., D. R. Mishra, and S. Pennings, 2019. Mapping Salt Marsh Soil Properties Using Imaging Spectroscopy. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 221-234.
- Zhang, C., S. Denka, and D. R. Mishra, 2018. Mapping Freshwater Marsh Species in the Wetlands of Lake Okeechobee using Very High-resolution Aerial Photography and Lidar Data. International Journal of Remote Sensing, 39: 5600-5618.
- Zhang, C., S. Denka, H. Cooper, and D. R. Mishra, 2018. Quantification of Sawgrass Marsh Aboveground Biomass in the Coastal Everglades Using Object-Based Ensemble Analysis and Landsat Data. Remote Sensing of Environment, 204, 366-379.
- Zhang, C., M. Smith, and C. Fang, 2018. Evaluation of Goddard’s LiDAR, Hyperspectral, and Thermal Data Products for Mapping Urban Land-cover Types. GIScience & Remote Sensing, 55, 90-109.
- Zhang, C., M. Smith, J. Lv, and C. Fang, 2017. Applying Time Series Landsat Data for Vegetation Change Analysis in the Florida Everglades Water Conservation Area 2A during 1996-2016. International Journal of Applied Earth Observations and Geoinformation, 57, 214-223.