Tao Liu
Tao Liu
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Comparing fully convolutional networks, random forest, support vector machine, and patch-based deep convolutional neural networks for object-based wetland mapping using images …
T Liu, A Abd-Elrahman, J Morton, VL Wilhelm
GIScience & remote sensing 55 (2), 243-264, 2018
Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product
Z Shao, J Cai, P Fu, L Hu, T Liu
Remote Sensing of Environment 235, 111425, 2019
Object-based classification of wetland vegetation using very high-resolution unmanned air system imagery
R Pande-Chhetri, A Abd-Elrahman, T Liu, J Morton, VL Wilhelm
European Journal of Remote Sensing 50 (1), 564-576, 2017
Change detection using deep learning approach with object-based image analysis
T Liu, L Yang, D Lunga
Remote Sensing of Environment 256, 112308, 2021
Deep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification
T Liu, A Abd-Elrahman
ISPRS Journal of Photogrammetry and Remote Sensing 139, 154-170, 2018
Forest biomass and carbon stock quantification using airborne LiDAR data: A case study over Huntington Wildlife Forest in the Adirondack Park
M Li, J Im, LJ Quackenbush, T Liu
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014
A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification
T Liu, J Im, LJ Quackenbush
ISPRS journal of photogrammetry and remote sensing 110, 34-47, 2015
A review of landcover classification with very-high resolution remotely sensed optical images—Analysis unit, model scalability and transferability
R Qin, T Liu
Remote Sensing 14 (3), 646, 2022
Sidewalk extraction using aerial and street view images
H Ning, X Ye, Z Chen, T Liu, T Cao
Environment and Planning B: Urban Analytics and City Science 49 (1), 7-22, 2022
Multi-view object-based classification of wetland land covers using unmanned aircraft system images
L Tao, AE Amr
Remote Sensing of Environment 216 (C), 122-138, 2018
An object-based image analysis method for enhancing classification of land covers using fully convolutional networks and multi-view images of small unmanned aerial system
T Liu, A Abd-Elrahman
Remote Sensing 10 (3), 457, 2018
A fully learnable context-driven object-based model for mapping land cover using multi-view data from unmanned aircraft systems
L Tao, AE Amr, Z Alina, D Bon, F Luke, S Smith
Remote Sensing of Environment 216, 328-344, 2018
Sensing population distribution from satellite imagery via deep learning: Model selection, neighboring effects, and systematic biases
X Huang, D Zhu, F Zhang, T Liu, X Li, L Zou
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
Deep learning classification of high-resolution drone images using the arcgis pro software: For374/fr444, 10/2021
A Abd-Elrahman, K Britt, T Liu
EDIS 2021 (5), 2021
Evaluating the potential of multi-view data extraction from small Unmanned Aerial Systems (UASs) for object-based classification for Wetland land covers
L Tao, AE Amr, D Bon, S Scot, J Morton, W Victor
GIScience & Remote Sensing, 2018
LandMOD ET mapper: A new matlab-based graphical user interface (GUI) for automated implementation of SEBAL and METRIC models in thermal imagery
N Bhattarai, T Liu
Environmental modelling & software 118, 76-82, 2019
A spectral three-dimensional color space model of tree crown health
WB Monahan, CE Arnspiger, P Bhatt, Z An, FJ Krist, T Liu, RP Richard, ...
PloS one 17 (10), e0272360, 2022
Integrating Deep Learning and Hydrodynamic Modeling to Improve the Great Lakes Forecast
P Xue, A Wagh, G Ma, Y Wang, Y Yang, T Liu, C Huang
Remote Sensing 14 (11), 2640, 2022
A Fully Automatic Method for Rapidly Mapping Impacted Area by Natural Disaster
T Liu, L Yang
2020 IEEE International Geoscience and Remote Sensing Symposium, 6906-6909, 2020
Towards misregistration-tolerant change detection using deep learning techniques with object-based image analysis
T Liu, L Yang, DD Lunga
Proceedings of the 27th ACM SIGSPATIAL international conference on advances …, 2019
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