| Mapping individual tree species in an urban forest using airborne lidar data and hyperspectral imagery C Zhang, F Qiu Photogrammetric Engineering & Remote Sensing 78 (10), 1079-1087, 2012 | 165 | 2012 |
| Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory C Zhang, Y Zhou, F Qiu Remote Sensing 7, 7892-7913, 2015 | 159 | 2015 |
| Combining object-based texture measures with a neural network for vegetation mapping in the Everglades from hyperspectral imagery C Zhang, Z Xie Remote Sensing of Environment 124, 310-320, 2012 | 149 | 2012 |
| Applying data fusion techniques for benthic habitat mapping and monitoring in a coral reef ecosystem C Zhang ISPRS Journal of Photogrammetry and Remote Sensing 104, 213-223, 2015 | 120 | 2015 |
| Quantification of sawgrass marsh aboveground biomass in the coastal Everglades using object-based ensemble analysis and Landsat data C Zhang, S Denka, H Cooper, DR Mishra Remote Sensing of Environment 204, 366-379, 2018 | 111 | 2018 |
| Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery C Zhang, D Selch, Z Xie, C Roberts, H Cooper, G Chen Estuarine, Coastal and Shelf Science 134, 88-97, 2013 | 96 | 2013 |
| Object-based vegetation mapping in the Kissimmee River watershed using HyMap data and machine learning techniques C Zhang, Z Xie Wetlands 33 (2), 233-244, 2013 | 84 | 2013 |
| Modeling land suitability/capability using fuzzy evaluation F Qiu, B Chastain, Y Zhou, C Zhang, H Sridharan GeoJournal 79 (2), 167-182, 2014 | 75 | 2014 |
| Combining hyperspectral and LiDAR data for vegetation mapping in the Florida Everglades C Zhang Photogrammetric Engineering & Remote Sensing 80 (8), 733-743, 2014 | 57 | 2014 |
| Object-based correction of LiDAR DEMs using RTK-GPS data and machine learning modeling in the coastal Everglades HM Cooper, C Zhang, SE Davis, TG Troxler Environmental Modelling & Software 112, 179-191, 2019 | 56 | 2019 |
| Modeling risk of mangroves to hurricanes: A case study of Hurricane Irma C Zhang, SD Durgan, D Lagomasino Estuarine, Coastal and Shelf Science, 2019 | 54* | 2019 |
| Mapping salt marsh soil properties using imaging spectroscopy C Zhang, D Mishra, S Pennings ISPRS Journal of Photogrammetry and Remote Sensing 148, 221-234, 2019 | 49 | 2019 |
| A point-based intelligent approach to areal interpolation C Zhang, F Qiu The Professional Geographer 63 (2), 262-276, 2011 | 48 | 2011 |
| Data fusion and classifier ensemble techniques for vegetation mapping in the coastal Everglades C Zhang, Z Xie Geocarto International 29 (3), 228-243, 2014 | 46 | 2014 |
| Fusing LIDAR and digital aerial photography for object-based forest mapping in the Florida Everglades C Zhang, Z Xie, D Selch GIScience & Remote Sensing 50 (5), 562-573, 2013 | 46 | 2013 |
| The development of an areal interpolation ArcGIS extension and a comparative study F Qiu, C Zhang, Y Zhou GIScience & Remote Sensing 49 (5), 644-663, 2012 | 46 | 2012 |
| Observing the coupling effect between warm pool and “rain pool” in the Pacific Ocean G Chen, C Fang, C Zhang, Y Chen Remote sensing of environment 91 (2), 153-159, 2004 | 42 | 2004 |
| Incorporating uncertainty of groundwater modeling in sea-level rise assessment: a case study in South Florida HM Cooper, C Zhang, D Selch Climatic Change 129 (1-2), 281-294, 2015 | 38 | 2015 |
| A Framework to Combine Three Remotely Sensed Data Sources for Vegetation Mapping in the Central Florida Everglades C Zhang, D Selch, H Cooper Wetlands 36 (2), 201-213, 2016 | 31 | 2016 |
| Mapping urban land cover types using object-based multiple endmember spectral mixture analysis C Zhang, H Cooper, D Selch, X Meng, F Qiu, SW Myint, C Roberts, Z Xie Remote Sensing Letters 5 (6), 521-529, 2014 | 29 | 2014 |
