程涛 教授

程涛，教授，博士生导师。国际数字地球学会中国国家委员会数字农业专业委员会副主任委员（2017/10-2022/10），中国农业生物技术学会植物表型组学专业委员会委员。2003年本科毕业于兰州大学，2006年于北京大学获硕士学位，2010年于加拿大阿尔伯塔大学获博士学位，2011-2013年在美国加州大学戴维斯分校从事博士后研究，2013年12月作为高层次引进人才到南京农业大学农学院工作，在国家信息农业工程技术中心从事作物生长监测理论与技术研究。十多年来一直围绕作物生理生化参数准确监测和病害早期探测等重要问题，研究监测方法和模型在不同作物、生育期之间的普适性，揭示作物生长参数动态变化的光谱响应机理。近年来发展了以连续小波光谱分析为特色的植被参数光谱监测理论与技术，在Remote Sensing of Environment等国际期刊发表了一系列重要成果。

主要学术成绩：1）创建了适用于作物生长参数高光谱估算的连续光谱小波分析技术，为作物生长监测领域提供了一种新颖、可靠的高光谱分析工具；2）阐明了基于干物质光谱指数的水稻生物量监测机理，为定量分析作物光谱—干物质积累转运—产量之间的关系提供了新思路；3）构建了适用于叶片二向反射率光谱的模型反演方法，发现叶片表面反射率对叶片生化参数自动化光谱监测的影响机制；4）首次在空间遥感平台监测果树水分的日内变化，实现了植物生长动 态的精密监测。

目前主持“十三五”国家重点研发计划项目——“粮食作物生长监测诊断与精确栽培技术”，另有国家自然科学基金等科研项目资助。共发表SCI收录论文20余篇，其中第一作者和通讯作者在遥感领域顶尖期刊Remote Sensing of Environment发表5篇，编辑出版英文著作一部。现为IEEE高级会员。2014年入选“江苏特聘教授”和江苏省“双创博士”计划，2014-2015 年担任国际期刊Remote Sensing客座编辑，2015年起任国际期刊ISPRS International Journal of Geo-Information编委。主讲的研究生全英文课《农业遥感原理与技术》入选2014年度江苏高校省级英文授课精品课程和2016年教育部第二批来华留学英语授课品牌课程。

部分论著：

Tian L, Xue B, Wang Z, Li D, Yao X, Cao Q, Zhu Y, Cao W, Cheng T*. Spectroscopic detection of rice leaf blast infection from asymptomatic to mild stages with integrated machine learning and feature selection. Remote Sensing of Environment. 2021, 257: 112350.

Wang W, Wu Y, Zhang Q, Zheng H, Yao X, Zhu Y, Cao W, Cheng T*. AAVI: A novel approach to estimating leaf nitrogen concentration in rice from unmanned aerial vehicle multispectral imagery at early and middle growth stages. IEEE Journal of Selected Topics in Applied Earth Observarions and Remote Sensing. 2021, 14: 6716-6728.

Yan Y, Zhang X, Li D, Zheng H, Yao X, Zhu Y, Cao W, Cheng T*. Laboratory shortwave infrared reflectance spectroscopy for estimating grain protein content in rice and wheat. International Journal of Remote Sensing. 2021, 42(12): 4467-4492.

Yang G, Yu W, Yao X, Zheng H, Cao Q, Zhu Y, Cao W, Cheng T*. 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. 2021, 102:102446.

Zhang X, Yang G, Xu X, Yao X, Zheng H, Zhu Y, Cao W, Cheng T*. An assessment of planet satellite imagery for county-wide mapping of rice planting areas in Jiangsu province, China with one-class classification approaches. International Journal of Remote Sensing. 2021, 42(19): 7610-7635.

Yan Y, Zhang X, Li D, Zheng H, Yao X, Zhu Y, Cao W, Cheng T*. Laboratory shortwave infrared reflectance spectroscopy for estimating grain protein content in rice and wheat. International Journal of Remote Sensing. 2021, 42(12): 4467-4492.

Alebele Y, Wang W, Yu W, Zhang X, Yao X, Tian Y, Zhu Y, Cao W, Cheng T*. Estimation of crop yield from combined optical and SAR imagery using Gaussian kernel regression. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021,14:10520-10534.

Li Dong, Chen J, XiaoZhang, YanYan, 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.

 Li D, Tian L, Wan Z, Jia M, Yao X, Tian Y, Zhu Y, Cao W*,Cheng T*.(2019).Assessment of unified models for estimating leaf chlorophyll content across directional-hemispherical reflectance and bidirectional reflectance spectra.Remote Sensing of Environment,  231: UNSP 111240.

Lu N, Zhou J, Han Z, Li D, Cao Q, Yao X, Tian Y, Zhu Y, Cao W,Cheng T*.(2019).Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system.Plant Methods, 15:17.

Li D,Cheng T*, Jia M, Zhou K, Lu N, Yao X, Tian Y, Zhu Y, Cao W.(2018).PROCWT: Coupling PROSPECT with continuous wavelet transform to improve the retrieval of foliar chemistry from leaf bidirectional reflectance spectra.Remote Sensing of Environment, 206:1-14.

 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.

Xu X, Ji X, Jiang J, Yao X, Tian Y, Zhu Y, Cao W, Cao Q, Yang H, Shi Z, Cheng T*.(2018).Evaluation of one-class support vector classification for mapping the paddy rice planting area in Jiangsu province of China from Landsat 8 OLI imagery.Remote Sensing, 10(4):546.

 Jiang J, Ji X, Yao X, Tian Y, Zhu Y, Cao W,Cheng T*.(2018).Evaluation of three techniques for correcting the spatial scaling bias of leaf area index.Remote Sensing, 10(2):221.

Cheng T, Song R, Li D, Zhou K, Zheng H, Yao X, Tian Y, Cao W, Zhu Y*.(2017).Spectroscopic Estimation of biomass in canopy components of paddy rice using dry matter and chlorophyll indices.Remote Sensing, 9(4):319.

Li, D.,Cheng, T.*,Zhou, K., Zheng, H., Yao, X., Tian, Y., Zhu, Y., & Cao, W. (2017). WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops.ISPRS Journal of Photogrammetry and Remote Sensing, 129, 103-117. 3.

 Zhou, K., Deng, X., Yao, X., Tian, Y., Cao, W., Zhu, Y.*, Ustin, S.L., &Cheng, T.*(2017). Assessing the spectral propertiesof sunlit and shaded components in rice canopies with near-ground imaging spectroscopy data.Sensors, 17, 578.

Zheng, H., Cheng, T., Yao, X., Deng, X., Tian,Y., Cao, W., & Zhu, Y. (2016). Detection of rice phenology through timeseries analysis of ground-based spectral index data. Field Crops Research,198, 131-139.

Cheng, T., Yang, Z., Inoue, Y., Zhu, Y., & Cao, W. (2016). Preface:recent advances in remote sensing for crop growth monitoring. RemoteSensing, 8, 116. (Editorial for Special Issue “Recent Advances inRemote Sensing for Crop Growth Monitoring”)

Yao, X., Huang, Y., Shang, G., Zhou, C., Cheng, T.,Tian, Y., Cao, W. & Zhu, Y. (2015). Evaluation of six algorithms to monitorwheat leaf nitrogen concentration. Remote Sensing, 7,14939-14966.

Chu, X., Guo, Y., He, J., Yao, X., Zhu, Y., Cao, W., Cheng,T. & Tian, Y. (2014). Comparison of different hyperspectralvegetation indices for estimating canopy leaf nitrogen accumulation in rice. AgronomyJournal, 106, 1911-1920.

Cheng, T., Riaño, D. & Ustin, S. L. (2014). Detectingdiurnal and seasonal variation in canopy water content of nut tree orchardsfrom airborne imaging spectroscopy data using continuous wavelet analysis. RemoteSensing of Environment, 143, 39-53.

Cheng, T., Rivard, B., Sánchez-Azofeifa, G. A., Féret, J. B., Jacquemoud,S. & Ustin, S. L. (2014). Deriving leaf mass per area (LMA) from foliarreflectance across a variety of plant species using continuous waveletanalysis. ISPRS Journal of Photogrammetry and Remote Sensing, 87, 28-38.

Cheng, T., Riaño, D., Koltunov, A., Whiting, M. L., Ustin, S. L.& Rodriguez, J. Detection of diurnal variation in orchard canopy watercontent using MODIS/ASTER airborne simulator (MASTER) data. (2013). RemoteSensing of Environment, 132, 1-12.

Cheng, T., Rivard, B., Sánchez-Azofeifa, G. A., Féret, J. B., Jacquemoud,S. & Ustin, S. L. (2012). Predicting leaf gravimetric water content fromfoliar reflectance across a range of plant species using continuous waveletanalysis. Journal of Plant Physiology, 169, 1134-1142.

Jin, H., Li, P., Cheng,T.&Song, B. (2012). Land cover classification usingCHRIS/PROBA images and multi-temporal texture.International Journal of Remote Sensing,33,101-119.

McKellar, R., Wolfe, A.,Muehlenbachs, K., Tappert, R., Engel, M.,Cheng, T., & Sánchez-Azofeifa, A. (2011). Insect outbreaks producedistinctive carbon isotope signatures in defensive resins and fossiliferousambers. Proceedings of the Royal Society B: Biological Sciences. doi:10.1098/rspb.2011.0276.

Cheng, T., Rivard, B., &Sánchez-Azofeifa, G. A. (2011). Spectroscopic determination of leaf watercontent using continuous wavelet analysis.Remote Sensing of Environment,115,659-670.

Cheng, T., Rivard, B.,Sánchez-Azofeifa, G. A., Feng, J. & Calvo-Polanco, M. (2010). Continuouswavelet analysis for the detection of green attack damage due to mountain pinebeetle infestation.Remote Sensing ofEnvironment, 114, 899-910.

Li, P., Yu, H.,& Cheng, T. (2009). Lithologic mapping usingASTER imagery and multivariate texture.Canadian Journal of Remote Sensing, 35, S117-S125.

李朋磊, 张骁, 王文辉, 郑恒彪, 姚霞, 朱艳, 曹卫星, 程涛*. 基于高光谱和激光雷达遥感的水稻产量监测研究. 中国农业科学, 2021, 54(14): 2965-2976.

张骁, 闫岩, 王文辉, 郑恒彪, 姚霞, 朱艳, 程涛*. 基于小波分析的水稻籽粒直链淀粉含量高光谱预测. 作物学报, 2021, 47(08): 1563-1580.

主持的主要科研项目：

1.国家重点研发计划项目，2016YFD0300600，粮食作物生长监测诊断与精确栽培技术，2016/01-2020/12

2.国家重点研发计划项目课题，2016YFD0300601，稻麦生长与生产力近地面实时监测预测，2016/01-2020/12

3.国家自然科学基金面上项目，31470084，基于小波分析的作物冠层结构与生理生化参数光谱响应分解研究，2015/01-2016/12

4.中国-挪威国际合作项目子课题，CHN-2152，减少环境影响和保障可持续食品安全和粮食安全的创新技术合作研究，2015/02-2017/06

5.中央高校基本科研业务费项目，KYRC201401，基于小波分析法的稻麦干物质遥感估测研究，2014/01-2016/12

每年接收愿意从事农业遥感研究的硕士和博士研究生，在基于卫星-无人机-地面平台的作物生长监测与生产力预测总体框架下从事创新性研究，热忱欢迎具有遥感与GIS、植物生理学、农业信息学或测绘工程专业背景者报考或申请，优先考虑刻苦钻研、勇于探索、勤于动手的学生！