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个人信息Personal Information
副高级
硕士生导师
教师英文名称：Minghan Cheng
教师拼音名称：Minghan Cheng
出生日期：1994-06-20
入职时间：2022-07-07
所在单位：农学院
学历：全日制学术型博士
办公地点：文汇路校区26号楼219
性别：男
学位：全日制学术学位博士
在职信息：在岗
毕业院校：河海大学
- 程明瀚,刘凯华,刘章鑫,徐俊增,张郑贤.Combination of Multiple Variables and Machine Learning for Regional Cropland Water and Carbon Fluxes Estimation: A Case Study in the Haihe River Basin.REMOTE SENSING,2024,16(17)
- 程明瀚,卢欣彤,刘章鑫,杨冠硕,张莉莉,孙斌倩,王知安.Accurate Characterization of Soil Moisture in Wheat Fields with an Improved Drought Index from Unmanned Aerial Vehicle Observations.AGRONOMY-BASEL,2024,14(8)
- 程明瀚,孙成明,聂臣巍,刘帅兵,余汛,白怡,金秀良,崔腾宇.Evaluation of UAV-based drought indices for crop water conditions monitoring: A case study of summer maize.AGRICULTURAL WATER MANAGEMENT,2023,287
- 程明瀚,殷大萌,吴文斌,崔宁波,聂臣巍,史梁生,金秀良,刘帅兵.A review of remote sensing estimation of crop water productivity: definition, methodology, scale, and evaluation.INTERNATIONAL JOURNAL OF REMOTE SENSING,2023,44(16)5033-5068.
- 程明瀚,缴锡云,石磊,潘纽拉斯,库玛尔,吴文斌,金秀良,聂臣巍.High-resolution crop yield and water productivity dataset generated using random forest and remote sensing.SCIENTIFIC DATA,2022,9(1)
- 程明瀚,殷大萌,吴文斌,崔宁波,聂臣巍,史梁生,金秀良,刘帅兵.A review of remote sensing estimation of crop water productivity: definition, methodology, scale, and evaluation.INTERNATIONAL JOURNAL OF REMOTE SENSING,2023,44(16)5033-5068.
- 程明瀚,孙成明,聂臣巍,刘帅兵,余汛,白怡,金秀良,崔腾宇.Evaluation of UAV-based drought indices for crop water conditions monitoring: A case study of summer maize.AGRICULTURAL WATER MANAGEMENT,2023,287
- 程明瀚,缴锡云,石磊,潘纽拉斯,库玛尔,吴文斌,金秀良,聂臣巍.High-resolution crop yield and water productivity dataset generated using random forest and remote sensing.SCIENTIFIC DATA,2022,9(1)
- Satellite time series data reveal interannual and seasonal spatiotemporal evapotranspiration patterns in China in response to effect factors.Agricultural Water Management,2021,
- Long time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validation.Earth System Science Data,2021,
- Using multimodal remote sensing data to estimate regional-scale soil moisture content: A case study of Beijing.Agricultural Water Management,2022,
- Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning.Agricultural Water Management,2022,
- Up-scaling the latent heat flux from instantaneous to daily-scale: A comparison of three methods.Journal of Hydrology: Regional Studies,2022,
- Combining multi-indicators with machine-learning algorithms for maize yield early prediction at the county-level in China.[SCI].Agricultural and Forest Meteorology,2022,
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