CZ  

Caiyun Zhang, Ph.D.

Associate Professor

Email  czhang3@fau.edu  
Phone (561) 297-2648  
Office: SE-488

Personal Web

Center for GISspacer graphic  

   
 

 

Education

Ph.D. in Geospatial Information Sciences (University of Texas at Dallas) 2010
Ph.D. in Ocean Remote Sensing (Ocean University of China) 2007
MS in Marine Geology (Ocean University of China) 2003
BS in Marine Geology (Ocean University of China) 1998

 

Research Interest

Hyperspectral and Lidar Remote Sensing
Coastal Vulnerability to Sea Level Rise and Hurricanes
Machine Learning Classification and Modeling
Object-Based Image Analysis 

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

 

Recent Publication

 

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.

Zhang, C., 2016. Multiscale Quantification of Urban Composition from EO-1/Hyperion Data Using Object-based Spectral Unmixing . International Journal of Applied Earth Observation and Geoinformation, 47, 153-162.

Zhang, C., D. Selch, and H. Cooper, 2016. A Framework to Combine Three Remotely Sensed Data Sources for Vegetation Mapping in the Central Florida Everglades . Wetlands, 36, 201-213.

Cooper, H., C. Zhang, and D. Selch, 2015. Incorporating Uncertainty of Groundwater Modeling in Sea-level Rise Assessment: A Case Study in South Florida. Climatic Change, 129, 281-294.

Zhang, C., Y. Zhou, and F. Qiu, 2015. Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory. Remote Sensing, 7, 7892-7913. (Open access:  http://www.mdpi.com/2072-4292/7/6/7892/html )

Zhang, C., 2015. Applying Data Fusion Techniques for Benthic Habitat Mapping and Monitoring in a Coral Reef Ecosystem . ISPRS Journal of Photogrammetry and Remote Sensing, 104, 213-223.

Zhang, C., 2014. Combining Hyperspectral and LiDAR Data for Vegetation Mapping in the Florida Everglades . Photogrammetric Engineering & Remote Sensing, 80, 733-743. (This paper won the 2015 John I. Davidson President’s Award from ASPRS)

Zhang, C., H. Cooper, D. Selch, et al., 2014. Mapping Urban Land Cover Types Using Object-based Multiple Endmember Spectral Mixture Analysis . Remote Sensing Letters, 5, 521-529.

Zhang, C., and Z. Xie, 2014. Data Fusion and Classifier Ensemble Techniques for Vegetation Mapping in the Coastal Everglades . Geocarto International, 29, 228-243.

Zhang, C., D. Selch, Z. Xie, C. Roberts, H. Cooper, and G. Chen, 2013. Object-based Benthic Habitat Mapping in the Florida Keys from Hyperspectral Imagery . Estuarine, Coastal and Shelf Science, 134, 88-97.

Zhang, C., Z. Xie, and D. Selch, 2013. Fusing LiDAR and Digital Aerial Photography for Object-based Forest Mapping in the Florida Everglades . GIScience & Remote Sensing, 50 (5), 562-573.

Zhang, C., and Z. Xie, 2013. Object-based Vegetation Mapping in the Kissimmee River Watershed Using HyMap Data and Machine Learning Techniques . Wetlands, 33 (2), 233-244.

 

 line

Return to Geosciences Home   

line