Year |
Citation |
Score |
2020 |
He M, Zhong L, Sandhu P, Zhou Y. Emulation of a Process-Based Salinity Generator for the Sacramento–San Joaquin Delta of California via Deep Learning Water. 12: 2088. DOI: 10.3390/W12082088 |
0.354 |
|
2019 |
Liu X, Yu L, Zhong L, Hao P, Wu B, Wang H, Yu C, Gong P. Spatial-temporal patterns of features selected using random forests: a case study of corn and soybeans mapping in the US International Journal of Remote Sensing. 40: 269-283. DOI: 10.1080/01431161.2018.1512769 |
0.455 |
|
2019 |
Zhong L, Hu L, Zhou H, Tao X. Deep learning based winter wheat mapping using statistical data as ground references in Kansas and northern Texas, US Remote Sensing of Environment. 233: 111411. DOI: 10.1016/J.Rse.2019.111411 |
0.53 |
|
2019 |
Zhong L, Hu L, Zhou H. Deep learning based multi-temporal crop classification Remote Sensing of Environment. 221: 430-443. DOI: 10.1016/J.Rse.2018.11.032 |
0.355 |
|
2018 |
Liu X, Yu L, Li W, Peng D, Zhong L, Li L, Xin Q, Lu H, Yu C, Gong P. Comparison of country-level cropland areas between ESA-CCI land cover maps and FAOSTAT data International Journal of Remote Sensing. 39: 6631-6645. DOI: 10.1080/01431161.2018.1465613 |
0.449 |
|
2017 |
Liu X, Yu L, Wang H, Zhong L, Lu H, Yu C, Gong P. Exploring the correlations between ten monthly climatic variables and the vegetation index of four different crop types at the global scale Remote Sensing Letters. 8: 752-760. DOI: 10.1080/2150704X.2017.1322732 |
0.364 |
|
2016 |
Zhong L, Yu L, Li X, Hu L, Gong P. Rapid corn and soybean mapping in US Corn Belt and neighboring areas. Scientific Reports. 6: 36240. PMID 27811989 DOI: 10.1038/Srep36240 |
0.51 |
|
2016 |
Zhong L, Hu L, Yu L, Gong P, Biging GS. Automated mapping of soybean and corn using phenology Isprs Journal of Photogrammetry and Remote Sensing. 119: 151-164. DOI: 10.1016/J.Isprsjprs.2016.05.014 |
0.68 |
|
2015 |
Dronova I, Gong P, Wang L, Zhong L. Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification Remote Sensing of Environment. 158: 193-206. DOI: 10.1016/J.Rse.2014.10.027 |
0.44 |
|
2014 |
Zhong L, Gong P, Biging GS. Efficient corn and soybean mapping with temporal extendability: A multi-year experiment using Landsat imagery Remote Sensing of Environment. 140: 1-13. DOI: 10.1016/J.Rse.2013.08.023 |
0.667 |
|
2013 |
Yu L, Wang J, Clinton N, Xin Q, Zhong L, Chen Y, Gong P. FROM-GC: 30 m global cropland extent derived through multisource data integration International Journal of Digital Earth. 6: 521-533. DOI: 10.1080/17538947.2013.822574 |
0.443 |
|
2012 |
Zhong L, Gong P, Biging GS. Phenology-based Crop Classification Algorithm and its Implications on Agricultural Water Use Assessments in California’s Central Valley Photogrammetric Engineering and Remote Sensing. 78: 799-813. DOI: 10.14358/Pers.78.8.799 |
0.596 |
|
2011 |
Zhong L, Hawkins T, Biging G, Gong P. A phenology-based approach to map crop types in the San Joaquin Valley, California International Journal of Remote Sensing. 32: 7777-7804. DOI: 10.1080/01431161.2010.527397 |
0.673 |
|
2009 |
Zhong L, Hawkins T, Holland K, Gong P, Biging GS. Satellite imagery can support water planning in the Central Valley California Agriculture. 63: 220-224. DOI: 10.3733/Ca.V063N04P220 |
0.662 |
|
1982 |
Zhong L. On the existence of extremal Teichmüller mappings Commentarii Mathematici Helvetici. 57: 511-517. DOI: 10.1007/BF02565872 |
0.309 |
|
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