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Zhang, C., 2020. Multi-sensor System Applications in the Everglades Ecosystem. Taylor and Francis Inc., ISBN:1498711774; ISBN-13: 9781498711777, 334 pages.


Selected Peer-reviewed Journal Articles


1)      Zhang, C., 2019. Combining Ikonos and Bathymetric LiDAR Data to Improve Reef Habitat Mapping in the Florida Keys. Papers in Applied Geography, DOI: 10.1080/23754931.2019.1694967.

2)      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. https://authors.elsevier.com/a/1Z2U7~1MBZMVU.

3)      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.

4)      Cooper, H., C. Zhang, S.E. Davis, and T.G. Troxler, 2019. Object-based correction of LiDAR DEMs using RTK-GPS data and machine learning modeling in the coastal Everglades. Environmental Modeling & Software, 112, 179-191.

5)      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, https://doi.org/10.1080/01431161.2018.1455242.

6)      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.

7)      Zhang, C., M. Smith, and C. Fang, 2018. Evaluation of Goddardís LiDAR, Hyperspectral, and Thermal Data Products for Mapping Urban Land-cover Types. GIScience & Remote Sensing, 55, 90-109.

8)      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.

9)      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.

10)  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.

11)  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)

12)  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.

13)  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 Presidentís Award from ASPRS)

14)  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.

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

16)  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.

17)  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.

18)  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.

19)  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.

20)  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. (This paper won the Early Career Paper Award of Remote Sensing Specialty Group (RSSG) of AAG, and the First Place of the 2013 ERDAS Award for Best Scientific Paper in Remote Sensing from ASPRS)

21)  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. (This paper won the First Place of Student Honors Paper Competition, Remote Sensing Specialty Group (RSSG) of AAG 2010)

22)  Zhang, C., Z. Xie, C. Roberts, L. Berry, and G. Chen, 2012. Salinity Assessment in Northeast Florida Bay Using Landsat TM Data. Southeastern Geographer, 52 (3), 267-281.

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