Florida Atlantic University

 FAU / Science / Geosciences / CGIS





GIS&RS Certificates

Minor in GIS

GIS/RS Courses

Research and Projects

Training and Workshops





Faculty affiliated with the Center for GIS have been actively involved various research activities.


  • 2008-2013 Everglades Digital Elevation Model and Digital Water Surface Model development through the USGS Everglades Depth Estimation Network (EDEN) project: Dr. Xie has been a PI on a series of EDEN projects funded by the USGS.

"The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level monitoring, ground-elevation modeling, and water-surface modeling that provides scientists and managers with current (1991-present), on-line water-depth information for the entire freshwater portion of the Greater Everglades."  (http://sofia.usgs.gov/eden/).

  • 2011-2014 Research and Technical Assistance for Assessing: Climate Change, Sea Level Rise and Salinity Dynamics in the Greater Everglades, funded by the USGS, PI, Len Berry, Co-PIs, Caiyun Zhang, Zhixiao Xie,
  • 2010-2011 Feasibility of modeling impacts of sea level rise on foraging habitat of the Little Blue Heron in the Great White Heron National Wildlife Refuge, Funded by US Fish and Wildlife Service, PI, Dale Gawlik, Co-PI, Zhixiao Xie
  • 2006-2007 Detect invasive plants in Florida coastal areas using an image retrieval approach and remote sensed data, Funded by the Florida Fish and Wildlife Conservation Commission (FFWC), PI, Zhixiao Xie, Co-PI, Charles Roberts
  • 2005-2007 Location Strategies for the Initial Hydrogen Refueling Infrastructure in Florida, Funded by Florida Hydrogen Initiative, Lee Lines, Michael Kuby, Ronald Schultz, Zhixiao Xie


1)     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.

2)     Zhang, C., 2014. Combining hyperspectral and LiDAR data for vegetation mapping in the florida everglades. Photogrammetric Engineering & Remote Sensing, 80, 733-743.

3)     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.

4)     Zhang, C., and Z. Xie, 2014. Data fusion and classifier ensemble techniques for vegetation mapping in the coastal everglades. Geocarto International, 29, 228-243.

5)     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.

6)     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.

7)     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.

8)     Xie, Z., C. Zhang, and L. Berry, 2013. Geographically weighted modeling of surface salinity in Florida Bay using Landsat TM data. Remote Sensing Letters, 4(1), 76-84.

9)     Xie, Z., L. Pearlstine, and D.E. Gawlik 2012. Develop a finer resolution DEM to support hydrological modeling and ecological study in the northern Everglades Freshwater Wetland. GIScience & Remote Sensing, 49(5) 664-686.

10)  Zhang, C. and Z. Xie 2012. Combining object-based texture measures with a neural network for vegetation mapping in the everglades from hyperspectral imagery. Remote Sensing of Environment, 124, 310-320.

11)  Zhang, C., Xie, Z., C. Roberts, and L. Berry 2012. Salinity assessment in the northeastern Florida Bay using Landsat TM Data. Southeast Geographer, 52(3), 267-281.

12)  Zhang, C., and F. Qiu, 2012a. Mapping individual tree species in an urban forest using airborne LiDAR data and hyperspectral imagery. Photogrammetric Engineering & Remote Sensing, 78 (10), 1079-1087.

13)  Zhang, C., and F. Qiu, 2012b. Hyperspectral image classification using an unsupervised neuro-fuzzy system. Journal of Applied Remote Sensing, 6, 063515, doi: 10.1117/1.JRS.6.063515.

14)  Xie, Z., Z.Liu, J. W. Jones, A. L. Higer, and P. A. Telis 2011. Landscape unit based digital elevation model development for the freshwater wetlands within the Arthur C. Marshall Loxahatchee National Wildlife Refuge, Southeastern Florida. Applied Geography,31 (1), 401-412

15)  Johnson, B. and Z. Xie, 2011. Unsupervised image segmentation evaluation and refinement using a multi-scale approach. ISPRS Journal of Photogrammetry and Remote Sensing, 66, 473-483.

16)  Zhang, C., and F. Qiu, 2011. A Point-based Intelligent Approach to Areal Interpolation. The Professional Geographer, 63, 262-276.

17)  Kuby, M., L. Lines, R. Schultz, Z. Xie, J. Kim, and S. Lim 2009. Optimization of hydrogen stations in florida using the flow-refueling location model, International Journal of Hydrogen Energy,34, 6045-6064.

18)  Xie, Z. and L. Bian 2009. Using spatial continuity and discontinuity information for content based geographic image retrieval. Geocarto International,24,3-23.

19)  Xie, Z., C. Roberts, and B. Johnson 2008. Object based target search using remotely sensed data: a case study in detecting invasive exotic Australian pine in South Florida. ISPRS Journal of Photogrammetry and Remote Sensing, 63, 647-660.

20)  Xie, Z. and J. Yan 2008. Kernel Density Estimation Of Traffic Accidents In A Network Space. Computers, Environment and Urban Systems,32, 396-406.

21)  Xie, Z. 2006. A framework for interpolating population surface at the residential housing unit level. GIScience & Remote Sensing, 43, 1-19.

22)  Xie, Z. 2004. A rotation and flip invariant algorithm for representing spatial continuity information of geographic images in content based image retrieval. Computers & Geosciences, 30, 1093-1104.

23)  Bian, L. and Z. Xie 2004. A spatial dependence approach to retrieving industrial complexes from digital images. Professional Geographer, 56 (3), 381-393.