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2020 – today
- 2024
[j13]Yuhao Wang
, Kuishuang Feng, Laixiang Sun, Yiqun Xie, Xiao-Peng Song:
Satellite-based soybean yield prediction in Argentina: A comparison between panel regression and deep learning methods. Comput. Electron. Agric. 221: 108978 (2024)- [j12]Mukti R. Subedi, Carlos Portillo-Quintero, Nancy E. McIntyre, Samantha S. Kahl, Robert D. Cox, Gad Perry, Xiao-Peng Song:
Ensemble Machine Learning on the Fusion of Sentinel Time Series Imagery with High-Resolution Orthoimagery for Improved Land Use/Land Cover Mapping. Remote. Sens. 16(15): 2778 (2024) - 2023
- [j11]Xiao-Peng Song:
The future of global land change monitoring. Int. J. Digit. Earth 16(1): 2279-2300 (2023) - 2022
- [j10]Amal H. Aljaddani, Xiao-Peng Song, Zhe Zhu:
Characterizing the Patterns and Trends of Urban Growth in Saudi Arabia's 13 Capital Cities Using a Landsat Time Series. Remote. Sens. 14(10): 2382 (2022) - 2021
- [i1]Chenxi Lin, Liheng Zhong, Xiao-Peng Song, Jinwei Dong, David B. Lobell, Zhenong Jin:
Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach. CoRR abs/2110.10275 (2021)
2010 – 2019
- 2019
- [j9]Jie Pei, Li Wang, Xiaoyue Wang, Zheng Niu, Maggi Kelly, Xiao-Peng Song, Ni Huang, Jing Geng, Haifeng Tian, Yang Yu, Shiguang Xu, Lei Wang, Qing Ying, Jianhua Cao:
Time Series of Landsat Imagery Shows Vegetation Recovery in Two Fragile Karst Watersheds in Southwest China from 1988 to 2016. Remote. Sens. 11(17): 2044 (2019) - [j8]Cheng Fu, Xiao-Peng Song, Kathleen Stewart:
Integrating Activity-Based Geographic Information and Long-Term Remote Sensing to Characterize Urban Land Use Change. Remote. Sens. 11(24): 2965 (2019) - 2018
- [j7]Rui Zhang, Chengquan Huang, Xiwu Zhan, Huiran Jin, Xiao-Peng Song:
Development of S-NPP VIIRS global surface type classification map using support vector machines. Int. J. Digit. Earth 11(2): 212-232 (2018) - 2017
- [j6]Xiao-Peng Song, Chengquan Huang, John R. Townshend:
Improving global land cover characterization through data fusion. Geo spatial Inf. Sci. 20(2): 141-150 (2017) - 2016
- [j5]Fujiang Liu, Chengquan Huang, Yong Pang, Mengxue Li, Dan-Xia Song, Xiao-Peng Song, Saurabh Channan, Joseph O. Sexton, Die Jiang, Ping Zhang, Yan Guo, Yao-Feng Li, John R. Townshend:
Assessment of the three factors affecting Myanmar's forest cover change using Landsat and MODIS vegetation continuous fields data. Int. J. Digit. Earth 9(6): 562-585 (2016) - [c2]Xiao-Peng Song:
A time-series model for characterizing continuous land cover change. IGARSS 2016: 3426-3429 - 2014
- [j4]Xiao-Peng Song, Chengquan Huang, Min Feng, Joseph O. Sexton, Saurabh Channan, John R. Townshend:
Integrating global land cover products for improved forest cover characterization: an application in North America. Int. J. Digit. Earth 7(9): 709-724 (2014) - [j3]Xiao-Peng Song, Chengquan Huang, Joseph O. Sexton, Saurabh Channan, John R. Townshend:
Annual Detection of Forest Cover Loss Using Time Series Satellite Measurements of Percent Tree Cover. Remote. Sens. 6(9): 8878-8903 (2014) - 2013
- [j2]Joseph O. Sexton, Xiao-Peng Song, Min Feng, Praveen Noojipady, Anupam Anand, Chengquan Huang, Do-Hyung Kim, Kathrine M. Collins, Saurabh Channan, Charlene M. DiMiceli, John R. Townshend:
Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error. Int. J. Digit. Earth 6(5): 427-448 (2013) - 2012
- [j1]John R. Townshend, Jeffrey G. Masek, Chengquan Huang, Eric F. Vermote, Feng Gao, Saurabh Channan, Joseph O. Sexton, Min Feng, Raghuram Narasimhan, Do-Hyung Kim, Kuan Song, Danxia Song, Xiao-Peng Song, Praveen Noojipady, Bin Tan, Matthew C. Hansen, Mengxue Li, Robert E. Wolfe:
Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges. Int. J. Digit. Earth 5(5): 373-397 (2012) - 2011
- [c1]Xiao-Peng Song, Chengquan Huang, Joseph O. Sexton, Min Feng, Raghuram Narasimhan, Saurabh Channan, John R. Townshend:
An assessment of global forest cover maps using regional higher-resolution reference data sets. IGARSS 2011: 752-755
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