郑恒彪，南京农业大学副教授，硕士生导师，入选江苏省青年科技人才托举工程。主要围绕农情遥感监测理论与技术开展科研工作。近十年来，以水稻和小麦作物为研究对象，在地面和无人机遥感尺度上，围绕作物生长关键参数（生物量、氮素营养指标、产量品质指标等）的特征光谱波段和敏感图谱参数、定量监测模型、示范应用等开展了深入系统的研究，集成建立了基于无人机遥感的作物生长参数快速监测与定量诊断技术体系。近五年来先后主持并参加国家自然科学基金、国家重点研发计划课题、江苏省自然科学基金、博士后特别资助、博士后面上项目等十余项，已发表核心期刊论文30多篇，合作出版专著1部；授权国家发明专利和美国专利各1项，获江西省科技进步二等奖1项。
部分论著： Zheng, H., Tang, W., Yang, T., Zhou, M., Guo, C., Cheng, T., Cao, W., Zhu, Y., Zhang, Y., & Yao, X. (2024). Grain protein content phenotyping in rice via hyperspectral imaging technology and a genome-wide association study. Plant Phenomics, 6. Mustafa, Ghulam+; Zheng, Hengbiao+; Li, Wei; Yin, Yuming; Wang, Yongqing; Zhou, Meng; Liu, Peng; Muhammad, Bilal; Jia, Haiyan; Li, Guoqiang; Cheng, Tao; Tian, Yongchao; Cao, Weixing; Zhu, Yan; Yao, Xia. (2023). Fusarium head blight monitoring in wheat ears using machine learning and multimodal data from asymptomatic to symptomatic periods. Frontiers in Plant Science, 13, 1102341. Zheng, H., Ji, W., Wang, W., Lu, J., Li, D., Guo, C., Yao, X., Tian, Y., Cao, W., Zhu, Y., Cheng T. (2022). Transferability of models for predicting rice grain yield from unmanned aerial vehicle (UAV) multispectral imagery across years, cultivars and sensors. Drones, 6, 423. Zheng, H., Ma, J., Zhou, M., Li, D., Yao, X., Cao, W., Zhu, Y., & Cheng, T. (2020a). Enhancing the nitrogen signals of rice canopies across critical growth stages through the integration of textural and spectral information from Unmanned Aerial Vehicle (UAV) multispectral imagery. Remote Sensing, 12, 957. Zheng, H., Zhou, X., He, J., Yao, X., Cheng, T., Zhu, Y., Cao, W., & Tian, Y. (2020b). Early season detection of rice plants using RGB, NIR-G-B and multispectral images from unmanned aerial vehicle (UAV). Computers and Electronics in Agriculture, 169, 105223. Zheng, H., Cheng, T., Zhou, M., Li, D., Yao, X., Tian, Y., Cao, W., & Zhu, Y. (2019). Improved estimation of rice aboveground biomass combining textural and spectral analysis of UAV imagery. Precision Agriculture, 20, 611-629. Zheng, H., Cheng, T., Li, D., Yao, X., Tian, Y., Cao, W., & Zhu, Y. (2018a). Combining unmanned aerial vehicle (UAV)-based multispectral imagery and ground-based hyperspectral data for plant nitrogen concentration estimation in rice. Frontiers in Plant Science, 9, 936. Zheng, H., Cheng, T., Li, D., Zhou, X., Yao, X., Tian, Y., Cao, W., & Zhu, Y. (2018b). Evaluation of RGB, color-infrared and multispectral images acquired from unmanned aerial systems for the estimation of nitrogen accumulation in rice. Remote Sensing, 10, 824. Zheng, H., Li, W., Jiang, J., Liu, Y., Cheng, T., Tian, Y., Zhu, Y., Cao, W., Zhang, Y., & Yao, X. (2018c). A comparative assessment of different modeling algorithms for estimating leaf nitrogen content in winter wheat using multispectral images from an unmanned aerial vehicle. Remote Sensing, 10, 2026. Zheng, H., Cheng, T., Yao, X., Deng, X., Tian, Y., Cao, W., & Zhu, Y. (2016). Detection of rice phenology through time series analysis of ground-based spectral index data. Field Crops Research, 198, 131-139. Wang, W., Zheng, H., Wu, Y., Yao, X., Zhu, Y., Cao, W., & Cheng, T. (2022). An assessment of background removal approaches for improved estimation of rice leaf nitrogen concentration with unmanned aerial vehicle multispectral imagery at various observation times. Field Crops Research, 283, 108543. Zhou, X., Zheng, H., Xu, X., He, J., Ge, X., Yao, X., Cheng, T., Zhu, Y., Cao, W., & Tian, Y. (2017). Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 246-255. Mustafa, G., Zheng, H., Khan, I.H., Tian, L., Jia, H., Li, G., Cheng, T., Tian, Y., Cao, W., Zhu, Y., & Yao, X. (2022). Hyperspectral reflectance proxies to diagnose in-field fusarium head blight in wheat with machine learning. Remote Sensing, 14, 2784. Lu, N., Wu, Y., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T. (2022). An assessment of multi-view spectral information from UAV-based color-infrared images for improved estimation of nitrogen nutrition status in winter wheat. Precision Agriculture. Li, D., Wang, X., Zheng, H., Zhou, K., Yao, X., Tian, Y., Zhu, Y., Cao, W., & Cheng, T. (2018). Estimation of area- and mass-based leaf nitrogen contents of wheat and rice crops from water-removed spectra using continuous wavelet analysis. Plant Methods, 14, 76. Jiang, J., Cai, W., Zheng, H., Cheng, T., Tian, Y., Zhu, Y., Ehsani, R., Hu, Y., Niu, Q., Gui, L., & Yao, X. (2019a). Using digital cameras on an unmanned aerial vehicle to derive optimum color vegetation indices for leaf nitrogen concentration monitoring in winter wheat. Remote Sensing, 11, 2667. Li, D., Chen, J.M., Yu, W., Zheng, H., Yao, X., Cao, W., Wei, D., Xiao, C., Zhu, Y., & Cheng, T. (2022). Assessing a soil-removed semi-empirical model for estimating leaf chlorophyll content. Remote Sensing of Environment, 282, 113284. Li, D., Chen, J.M., Zhang, X., Yan, Y., Zhu, J., Zheng, H., Zhou, K., Yao, X., Tian, Y., Zhu, Y., Cheng, T., & Cao, W. (2020). Improved estimation of leaf chlorophyll content of row crops from canopy reflectance spectra through minimizing canopy structural effects and optimizing off-noon observation time. Remote Sensing of Environment, 248, 111985. Yang, G., Yu, W., Yao, X., Zheng, H., Cao, Q., Zhu, Y., Cao, W., & Cheng, T. (2021). AGTOC: A novel approach to winter wheat mapping by automatic generation of training samples and one-class classification on Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation, 102, 102446. 吉文翰，郑恒彪*，王迪，唐伟杰，郭彩丽，姚霞，江冲亚，朱艳，曹卫星，程涛. 基于无人机影像和卷积神经网络的水稻育种材料产量预测研究，南京农业大学学报，2024。 郑恒彪，吉文翰，郭彩丽，邱小雷，姚霞，江冲亚，朱艳，曹卫星，程涛*. 无人机遥感作物估产研究进展，南京农业大学学报，2024。
代表性发明专利： 1、Yan Zhu; Hengbiao Zheng; Tao Cheng; Xia Yao;Yongchao Tian; Weixing Cao. Method for estimating aboveground biomass of rice based on multi-spectral images of Unmanned Aerial Vehicle. No. US11029251 B2. 2、朱艳、郑恒彪、程涛、姚霞、田永超、曹卫星。一种基于无人机多光谱影像的水稻地上部生物量估测方法。专利号：ZL201811312158.7. 3、程涛、张巧凤、郑恒彪、姚霞、田永超、朱艳、曹卫星。一种基于同期卫星影像的多架次无人机影像相对辐射校正方法。专利号：ZL202110242020.X. 4、程涛、王文辉、郑恒彪、吴亚鹏、姚霞、朱艳、曹卫星。一种基于无人机多光谱影像消除水稻冠层背景效应并提升叶片氮浓度监测精度的方法。专利申请号：ZL202210119047.4. 科研项目：
1、水稻生产智能决策模型与精确作业系统，国家重点研发计划子课题，2024.12-2027.11，主持，在研； 2、烟叶产质量预测模型构建，河南省烟草公司科技项目，2023.7-2026.6，主持，在研； 3、农作物关键农情参量实时感知和技术研究，国家重点研发计划子课题，2022.7-2027.7，主持，在研； 4、基于无人机多源遥感影像和深度学习的水稻种质资源产量估测研究，中国博士后科学基金特别资，2022.07-2024.06，主持，结题； 5、基于无人机多源遥感影像和深度学习的大田水稻籽粒蛋白质含量预测研究，国家自然科学基金青年项，2022.01-2024.12，主持，结题； 6、作物模型与高分辨率遥感融合的作物产量及品质动态预测方法，国家重点研发计划子课题，2021.02-2023.03，主持，结题； 7、基于无人机多光谱影像的水稻蛋白质含量预测研究，中国博士后面上项目，2019.07-2022.06，主持，结题； 8、基于无人机多传感器的水稻产量预测研究，江苏省自然科学基金，2019.07-2022.06，主持，结题。
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