Liheng Zhong

Deep learning based multi-temporal crop classification

Hang Zhou, Lina Hu, Liheng Zhong, 2019, Remote Sensing of Environment.

Automated mapping of soybean and corn using phenology

Gregory S. Biging, Peng Gong, Lina Hu, 2016 .

Classification under Data Contamination with Application to Remote Sensing Image Mis-registration pdf

Peng Gong, Donghui Yan, Aiyou Chen, 2011, ArXiv.

Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification

Lin Wang, Peng Gong, Iryna Dronova, 2015 .

Deep learning based winter wheat mapping using statistical data as ground references in Kansas and northern Texas, US

Xin Tao, Hang Zhou, Lina Hu, 2019, Remote Sensing of Environment.

FROM-GC: 30 m global cropland extent derived through multisource data integration

Le Yu, Jie Wang, Qinchuan Xin, 2013, Int. J. Digit. Earth.

Deep Neural Networks for Mapping Integrated Crop-Livestock Systems Using Planetscope Time Series

Rubens A. C. Lamparelli, Gleyce Kelly Dantas Araújo Figueiredo, Liheng Zhong, 2021, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS.

Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach pdf

Chenxi Lin, David B. Lobell, Liheng Zhong, 2021, Remote Sensing of Environment.

Spatial-temporal patterns of features selected using random forests: a case study of corn and soybeans mapping in the US

Pengyu Hao, Le Yu, Chaoqing Yu, 2018, International Journal of Remote Sensing.

Satellite imagery can support water planning in the Central Valley

Peng Gong, Gregory S. Biging, Liheng Zhong, 2009 .