| Deep learning based multi-temporal crop classification L Zhong, L Hu, H Zhou Remote sensing of environment 221, 430-443, 2019 | 734 | 2019 |
| Efficient corn and soybean mapping with temporal extendability: A multi-year experiment using Landsat imagery L Zhong, P Gong, GS Biging Remote Sensing of Environment 140, 1-13, 2014 | 350 | 2014 |
| Automated mapping of soybean and corn using phenology L Zhong, L Hu, L Yu, P Gong, GS Biging ISPRS Journal of Photogrammetry and Remote Sensing 119, 151-164, 2016 | 202 | 2016 |
| Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification I Dronova, P Gong, L Wang, L Zhong Remote Sensing of Environment 158, 193-206, 2015 | 153 | 2015 |
| 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 | 151 | 2013 |
| A phenology-based approach to map crop types in the San Joaquin Valley, California L Zhong, T Hawkins, G Biging, P Gong International Journal of Remote Sensing 32 (22), 7777-7804, 2011 | 126 | 2011 |
| Deep learning based winter wheat mapping using statistical data as ground references in Kansas and northern Texas, US L Zhong, L Hu, H Zhou, X Tao Remote Sensing of Environment 233, 111411, 2019 | 76 | 2019 |
| Rapid corn and soybean mapping in US Corn Belt and neighboring areas L Zhong, L Yu, X Li, L Hu, P Gong Scientific reports 6 (1), 36240, 2016 | 73 | 2016 |
| Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California’s Central Valley L Zhong, P Gong, GS Biging Photogrammetric Engineering & Remote Sensing 78 (8), 799-813, 2012 | 71 | 2012 |
| Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning F Zhao, R Sun, L Zhong, R Meng, C Huang, X Zeng, M Wang, Y Li, ... Remote Sensing of Environment 269, 112822, 2022 | 63 | 2022 |
| Comparison of country-level cropland areas between ESA-CCI land cover maps and FAOSTAT data X Liu, L Yu, W Li, D Peng, L Zhong, L Li, Q Xin, H Lu, C Yu, P Gong International Journal of Remote Sensing 39 (20), 6631-6645, 2018 | 63 | 2018 |
| DKDFN: Domain knowledge-guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classification Y Li, Y Zhou, Y Zhang, L Zhong, J Wang, J Chen ISPRS Journal of Photogrammetry and Remote Sensing 186, 170-189, 2022 | 62 | 2022 |
| Early-and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach C Lin, L Zhong, XP Song, J Dong, DB Lobell, Z Jin Remote Sensing of Environment 274, 112994, 2022 | 56 | 2022 |
| Mapping corn dynamics using limited but representative samples with adaptive strategies Y Wen, X Li, H Mu, L Zhong, H Chen, Y Zeng, S Miao, W Su, P Gong, B Li, ... ISPRS Journal of Photogrammetry and Remote Sensing 190, 252-266, 2022 | 26 | 2022 |
| Spatial-temporal patterns of features selected using random forests: A case study of corn and soybeans mapping in the US X Liu, L Yu, L Zhong, P Hao, B Wu, H Wang, C Yu, P Gong International journal of remote sensing 40 (1), 269-283, 2019 | 20 | 2019 |
| Wheat yield estimation using remote sensing data based on machine learning approaches E Cheng, B Zhang, D Peng, L Zhong, L Yu, Y Liu, C Xiao, C Li, X Li, ... Frontiers in Plant Science 13, 1090970, 2022 | 19 | 2022 |
| Efficient crop type mapping based on remote sensing in the Central Valley, California L Zhong University of California, Berkeley, 2012 | 13 | 2012 |
| Cret: Cross-modal retrieval transformer for efficient text-video retrieval K Ji, J Liu, W Hong, L Zhong, J Wang, J Chen, W Chu Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 12 | 2022 |
| Emulation of a process-based salinity generator for the sacramento–san joaquin delta of california via deep learning M He, L Zhong, P Sandhu, Y Zhou Water 12 (8), 2088, 2020 | 11 | 2020 |
| Satellite imagery can support water planning in the Central Valley L Zhong, T Hawkins, K Holland, P Gong, GS Biging California Agriculture 63 (4), 2009 | 7 | 2009 |
Peng GongThe University of Hong Kong，http://orcid.org/0000-0003-1513-3765Verifierad e-postadress på hku.hk
