|Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data|
P Gong, J Wang, L Yu, Y Zhao, Y Zhao, L Liang, Z Niu, X Huang, H Fu, ...
International Journal of Remote Sensing 34 (7), 2607-2654, 2013
|Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery|
Q Yu, P Gong, N Clinton, G Biging, M Kelly, D Schirokauer
Photogrammetric Engineering & Remote Sensing 72 (7), 799-811, 2006
|Accuracy assessment measures for object-based image segmentation goodness|
N Clinton, A Holt, J Scarborough, LI Yan, P Gong
Photogramm. Eng. Remote Sens 76 (3), 289-299, 2010
|Prehistoric fire area and emissions from California's forests, woodlands, shrublands, and grasslands|
SL Stephens, RE Martin, NE Clinton
Forest Ecology and Management 251 (3), 205-216, 2007
|MODIS detected surface urban heat islands and sinks: Global locations and controls|
N Clinton, P Gong
Remote Sensing of Environment 134, 294-304, 2013
|Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine|
H Huang, Y Chen, N Clinton, J Wang, X Wang, C Liu, P Gong, J Yang, ...
Remote Sensing of Environment 202, 166-176, 2017
|Landscape analysis of wetland plant functional types: The effects of image segmentation scale, vegetation classes and classification methods|
I Dronova, P Gong, NE Clinton, L Wang, W Fu, S Qi, Y Liu
Remote Sensing of Environment 127, 357-369, 2012
|FROM-GC: 30 m global cropland extent derived through multisource data integration|
L Yu, J Wang, N Clinton, Q Xin, L Zhong, Y Chen, P Gong
International Journal of Digital Earth 6 (6), 521-533, 2013
|Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017|
B Chen, B Xu, Z Zhu, C Yuan, HP Suen, J Guo, N Xu, W Li, Y Zhao, ...
Sci Bull 64, 370-373, 2019
|The global distribution and trajectory of tidal flats|
NJ Murray, SR Phinn, M DeWitt, R Ferrari, R Johnston, MB Lyons, ...
Nature 565 (7738), 222-225, 2019
|Rainforest-initiated wet season onset over the southern Amazon|
JS Wright, R Fu, JR Worden, S Chakraborty, NE Clinton, C Risi, Y Sun, ...
Proceedings of the National Academy of Sciences 114 (32), 8481-8486, 2017
|A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform|
B Chen, X Xiao, X Li, L Pan, R Doughty, J Ma, J Dong, Y Qin, B Zhao, ...
ISPRS Journal of Photogrammetry and Remote Sensing 131, 104-120, 2017
|An artificial neural network model for estimating crop yields using remotely sensed information|
D Jiang, X Yang, N Clinton, N Wang
International Journal of Remote Sensing 25 (9), 1723-1732, 2004
|Fuel treatment effects on stand-level carbon pools, treatment-related emissions, and fire risk in a Sierra Nevada mixed-conifer forest|
SL Stephens, JJ Moghaddas, BR Hartsough, EEY Moghaddas, ...
Canadian Journal of Forest Research 39 (8), 1538-1547, 2009
|Stacked Autoencoder-based deep learning for remote-sensing image classification: a case study of African land-cover mapping|
W Li, H Fu, L Yu, P Gong, D Feng, C Li, N Clinton
International journal of remote sensing 37 (23), 5632-5646, 2016
|Automated methods for measuring DBH and tree heights with a commercial scanning lidar|
H Huang, Z Li, P Gong, X Cheng, N Clinton, C Cao, W Ni, L Wang
Photogrammetric Engineering & Remote Sensing 77 (3), 219-227, 2011
|Modeling population density using land cover data|
Y Tian, T Yue, L Zhu, N Clinton
Ecological modelling 189 (1-2), 72-88, 2005
DC Parker, MF Wolff
Science and Technology, 1965
|Using Landsat and nighttime lights for supervised pixel-based image classification of urban land cover|
R Goldblatt, MF Stuhlmacher, B Tellman, N Clinton, G Hanson, ...
Remote Sensing of Environment 205, 253-275, 2018
|Reduction of atmospheric and topographic effect on Landsat TM data for forest classification|
H Huang, P Gong, N Clinton, F Hui
International Journal of Remote Sensing 29 (19), 5623-5642, 2008