程涛 教授

程涛，教授，博士生导师。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国家信息农业工程技术中心工作，研究方向包括遥感大数据与智能化作物制图、作物遥感机理建模、多尺度农情参数遥感反演等。教育部长江学者特聘教授，农业农村部神农青年英才，“十三五”国家重点研发计划项目首席专家，国家自然科学基金创新研究群体骨干成员，江苏特聘教授。目前担任国家信息农业工程技术中心副主任，同时担任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、中国农学会农业信息分会副主任委员、中国植物营养与肥料学会智慧耕肥专委会副主任委员，江苏省遥感与地理信息系统学会常务理事，国际期刊IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing、Precision Agriculture副主编等学术兼职。

主持国家重点研发计划项目与课题，以及国家自然科学基金等科研项目。近年来以水稻和小麦为主要研究对象，在大规模农田与作物识别、作物生长参数高精度反演、稻瘟病早期监测与病情估算、产量季中与季末估测等方面取得重要进展，为我国粮食安全生产的规模化监测、数字化预测与智能化管理等提供有力支撑。以第一或通讯作者在Remote Sens. Environ.等国际著名期刊发表论文50余篇，获得中国作物学会青年科技奖、江苏省优秀博士学位论文指导老师、2021年度RSE最佳审稿人等荣誉。主讲的研究生全英文课《农业遥感原理与技术》入选教育部来华留学英语授课品牌课程。

一、代表性论文(*表示通讯作者)：

Xue, B., Kong, Y., Zarco-Tejada, P.J., Tian, L., Poblete, T., Wang, X., Zheng, H., Jiang, C., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2026). Mitigating the phenological influence on spectroscopic quantification of rice blast disease severity with extended PROSAIL simulations. Remote Sensing of Environment, 332.

Yu, W., Xiong, Y., Li, X., Zheng, H., Jiang, C., Yao, X., Zhu, Y.*, Cao, W., Qiu, L., Song, L., & Cheng, T.* (2026). Rice yield prediction in unseen years at field level with high-resolution gross primary productivity derived from Sentinel-2 imagery. Remote Sensing of Environment, 332, 115061.

Tian, L., Ustin, S.L., Xue, B., Zarco-Tejada, P.J., Jin, Y., Yao, X., Zhu, Y.*, Cao, W., & Cheng, T.* (2025). Visualizing the pre-visual: Rice blast infection signals revealed. Remote Sensing of Environment, 328, 114905.

Sun, H., Wei, Z., Yu, W., Yang, G., She, J., Zheng, H., Jiang, C., Yao, X., Zhu, Y., Cao, W., Cheng, T.*, & Ali, I. (2025). SIDEST: A sample-free framework for crop field boundary delineation by integrating super-resolution image reconstruction and dual edge-corrected Segment Anything model. Computers and Electronics in Agriculture, 230, 109897. (Download the crop field dataset at https://doi.org/10.5281/zenodo.14257921 and the software at https://doi.org/10.5281/zenodo.14263411.）

Xue, B., Tian, L., Zarco-Tejada, P.J., Kong, Y., Poblete, T., Wang, X., Zheng, H., Jiang, C., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2025). A two-step approach to mitigating phenological influences on spectroscopic detection of rice blast and removing pseudo severity estimates in healthy plants. Computers and Electronics in Agriculture, 236, 110458.

Yan, Y., Li, D., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2025). Integration of multiscale spectral features as the intermediate variables for Improved prediction of grain protein concentration in winter wheat. IEEE Transactions on Geoscience and Remote Sensing, 63, 1-18.

Yang, G., Li, X., Xiong, Y., He, M., Zhang, L., Jiang, C., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2025). Annual winter wheat mapping for unveiling spatiotemporal patterns in China with a knowledge-guided approach and multi-source datasets. ISPRS Journal of Photogrammetry and Remote Sensing, 225, 163-179. (Download the ChinaWheat30L product at https://zenodo.org/records/15124014.)

Wu, Y., Yu, W., Gu, Y., Zhang, Q., Xiong, Y., Zheng, H., Jiang, C., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2025). Accurate estimation of grain number per panicle in winter wheat by synergistic use of UAV imagery and meteorological data. International Journal of Applied Earth Observation and Geoinformation, 136, 104320.

Li, D., Chen, J.M., Yu, W., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2025). Corrigendum to “A chlorophyll-constrained semi-empirical model for estimating leaf area index using a red-edge vegetation index” [Comput. Electron. Agric. 220 (2024) 108891]. Computers and Electronics in Agriculture, 229, 109722.

Yu, W., Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., Qiu, L., Cheng, T.*, Zhang, Y., & Zhou, Y. (2024). HIDYM: A high-resolution gross primary productivity and dynamic harvest index based crop yield mapper. Remote Sensing of Environment, 311, 114301.

Yang, G., Li, X., Xiong, Y., He, M., Wang, X., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2024). Winter wheat mapping without ground labels via automated knowledge transfer across regions and years. Computers and Electronics in Agriculture, 227, 109536.

Li, D., Chen, J.M., Yu, W., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2024). A chlorophyll-constrained semi-empirical model for estimating leaf area index using a red-edge vegetation index. Computers and Electronics in Agriculture, 220, 108891.

Li, D., Wu, Y., Berger, K., Kuang, Q., Feng, W., Chen, J.M., Wang, W., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2024). Estimating canopy nitrogen content by coupling PROSAIL-PRO with a nitrogen allocation model. International Journal of Applied Earth Observation and Geoinformation, 135, 104280.

Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2024). Assessing the sensitivity of semiempirical models to spectral data quality and sensor settings when estimating leaf chlorophyll content. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 4062-4070.

Tian, L., Wang, Z., Xue, B., Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). A disease-specific spectral index tracks Magnaporthe oryzae infection in paddy rice from ground to space. Remote Sensing of Environment, 285, 113384.

Yang, G., Li, X., Liu, P., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). Automated in-season mapping of winter wheat in China with training data generation and model transfer. ISPRS Journal of Photogrammetry and Remote Sensing, 202, 422-438. (Download the ChinaWheat10 product at https://doi.org/10.5281/zenodo.8119065.)

Yan, Y., Li, D., Kuang, Q., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). Integration of canopy water removal and spectral triangle index for improved estimations of leaf nitrogen and grain protein concentrations in winter wheat. IEEE Transactions on Geoscience and Remote Sensing, 61, 1-18.

Li, D., Yu, W., Zheng, H., Guo, C., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). Towards practical semi-empirical models for the estimation of leaf and canopy water contents from hyperspectral reflectance. Computers and Electronics in Agriculture, 214, 108309.

Yu, W., Yang, G., Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., Qiu, L., & Cheng, T.* (2023). Improved prediction of rice yield at field and county levels by synergistic use of SAR, optical and meteorological data. Agricultural and Forest Meteorology, 342, 109729.

Wu, Y., Wang, W., Gu, Y., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). SPSI: A novel composite index for estimating panicle number in winter wheat before heading from UAV multispectral imagery. Plant Phenomics, 5, 0087.

Xue, B., Tian, L., Wang, Z., Wang, X., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). Quantification of rice spikelet rot disease severity at organ scale with proximal imaging spectroscopy. Precision Agriculture, 24, 1049-1071.

Li, D., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2023). Semi-empirical models for estimating canopy chlorophyll content: The importance of prior information. Remote Sensing Letters, 14, 1111-1118.

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., Yan, Y., Zheng, H., Yao, X., Zhu, Y., Cao, W.*, & Cheng, T.* (2022). Estimating leaf nitrogen content by coupling a nitrogen allocation model with canopy reflectance. Remote Sensing of Environment, 283, 113314.

Jiang, J., Zhang, Q., Wang, W., Wu, Y., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T.* (2022). MACA: A relative radiometric correction method for multiflight unmanned aerial vehicle images based on concurrent satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14.

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, 23, 1653-1674.

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.

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.

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

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.

Wang, W., Wu, Y., Zhang, Q., Zheng, H., Yao, X., Zhu, Y., Cao, W., & Cheng, T. (2021). 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 Observations and Remote Sensing, 14, 6716-6728.

Alebele, Y., Wang, W., Yu, W., Zhang, X., Yao, X., Tian, Y., Zhu, Y., Cao, W., & Cheng, T.* (2021). 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, 14, 10520-10534.

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

Zhang, X., Yang, G., Xu, X., Yao, X., Zheng, H., Zhu, Y., Cao, W., & Cheng, T.* (2021). 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, 42, 7610-7635.

Cheng, T., Ji, X., Yang, G., Zheng, H., Ma, J., Yao, X., Zhu, Y., & Cao, W.* (2020). DESTIN: A new method for delineating the boundaries of crop fields by fusing spatial and temporal information from WorldView and Planet satellite imagery. Computers and Electronics in Agriculture, 178, 105787.

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.

Li, P., Zhang, X., Wang, W., Zheng, H., Yao, X., Tian, Y., Zhu, Y., Cao, W., Chen, Q., & Cheng, T.* (2020). Estimating aboveground and organ biomass of plant canopies across the entire season of rice growth with terrestrial laser scanning. International Journal of Applied Earth Observation and Geoinformation, 91, 102132.

Jiang, J., Zhang, Q., Yao, X., Tian, Y., Zhu, Y., Cao, W., & Cheng, T.* (2020). HISTIF: A new spatiotemporal image fusion method for high-resolution monitoring of crops at the subfield level. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4607-4626.

Alebele, Y., Zhang, X., Wang, W., Yang, G., Yao, X., Zheng, H., Zhu, Y., Cao, W., & Cheng, T.* (2020). Estimation of canopy biomass components in paddy rice from combined optical and SAR data using multi-target Gaussian regressor stacking. Remote Sensing, 12, 2564.

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, 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. (WoS Highly Cited Paper)

Lu, N., Wang, W., Zhang, Q., Li, D., Yao, X., Tian, Y., Zhu, Y., Cao, W., Baret, F., Liu, S., & Cheng, T.* (2019). Estimation of nitrogen nutrition status in winter wheat from unmanned aerial vehicle based multi-angular multispectral imagery. Frontiers in Plant Science, 10, 1601.

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.

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.

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, 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, 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, 319.

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

Cheng, T., Yang, Z., Inoue, Y., Zhu, Y., & Cao, W. (2016). Preface: recent advances in remote sensing for crop growth monitoring. Remote Sensing, 8, 116.

Cheng, T., Riaño, D. & Ustin, S. L. (2014). Detecting diurnal and seasonal variation in canopy water content of nut tree orchards from airborne imaging spectroscopy data using continuous wavelet analysis. Remote Sensing 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 foliar reflectance across a variety of plant species using continuous wavelet analysis. 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 water content using MODIS/ASTER airborne simulator (MASTER) data. (2013). Remote Sensing 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 from foliar reflectance across a range of plant species using continuous wavelet analysis. Journal of Plant Physiology, 169, 1134-1142.

Cheng, T., Rivard, B., & Sánchez-Azofeifa, G. A. (2011). Spectroscopic determination of leaf water content 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). Continuous wavelet analysis for the detection of green attack damage due to mountain pine beetle infestation. Remote Sensing of Environment, 114, 899-910.

薛博文, 孔媛媛, 田龙, 王雪, 姚霞, 朱艳, 曹卫星, & 程涛* (2024). 两类真菌病害的特异性叶片光谱响应与监测精度对比研究. 遥感学报, 28, 2485-2499

李朋磊, 张骁, 王文辉,郑恒彪,姚霞,朱艳,曹卫星,程涛*. (2021). 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, 54, 2965-2976

张骁, 闫岩, 王文辉, 郑恒彪, 姚霞, 朱艳, 程涛*. (2021). 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, 47, 1563-1580

姬旭升，李旭，万泽福，姚霞，朱艳，程涛*. (2019). 基于高空间分辨率卫星影像的新疆阿拉尔市棉花与枣树分类. 中国农业科学, 52, 997-1008.

二、合编著作：

1. 曹卫星，程涛，朱艳，姚霞，等. 2020. 作物生长光谱监测. 北京: 科学出版社.

2. Cheng, T., Zhu, Y., Li, D., Yao, X, & Zhou, K. (2018). Hyperspectral remote sensing of leaf nitrogen concentration in cereal crops. In P. S. Thenkabail, J. Lyon, & A. Huete (Eds.), Hyperspectral Remote Sensing of Vegetation, Second Edition, Four Volume Set, Volume 2. Boca Raton, FL: CRC Press.

三、国家发明专利：

1. 程涛、杨高翔、李兴荣、姚霞、朱艳、曹卫星. 一种基于训练样本自动化提取的大尺度冬小麦早期识别方法：中国，ZL 202311495045.6.

2. 程涛、李栋、姚霞、朱艳、曹卫星. 一种基于氮分配理论的稻麦叶片氮含量高光谱估算方法：中国，ZL202211301573.9.

3. 程涛、薛博文、田龙、姚霞、朱艳、曹卫星. 一种基于新型三波段光谱指数的水稻穗腐病病情严重度估算方法：中国，ZL202310236635.0.

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：中国，ZL202210119047.4.

5. 程涛、张巧凤、郑恒彪、姚霞、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：中国，ZL202110242020.X.

6. 程涛、江佳乐、姬旭升、姚霞、田永超、朱艳、曹卫星.一种面向田块尺度作物生长监测的遥感影像时空融合方法：中国，ZL201811312555.4.

7. 程涛、李栋、姚霞、田永超、朱艳、曹卫星.一种基于连续小波分析的水稻反射光谱红边位置提取方法：中国, ZL201710205193.8.

8. 曹卫星、李栋、程涛、姚霞、朱艳. 一种基于冠层组分光谱分离的土壤影响消除与小麦叶片叶绿素含量高精度估算方法：中国，ZL202211163318.2.

9. 朱艳、周凯、程涛、曹卫星、姚霞、田永超.一种基于近地面高光谱影像的水稻阴阳叶穗识别方法：中国，ZL201611020653.1.

10. 姚霞、朱艳、程涛、司海洋、田永超、马吉锋、张羽、邱小雷、王雪、曹卫星.一种基于连续小波分析建立小麦叶干重定量模型的方法：中国，ZL201611116173.5.

11. 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：中国，ZL201811312158.7.

12. 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; United States, US11029251B2.

四、科研项目：

1.科技部，国家重点研发计划课题，2023YFB3906202，全球主要农作物农情与环境参数高精度遥感反演，2023-12至2026-11，300万元，在研，主持

2.科技部，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至2020-12，6000万元，结题，主持

3.国家自然科学基金委员会，面上项目，41871259，基于近距离成像高光谱的水稻叶瘟病早期探测机理与方法研究，2019-01至2022-12，72万元，结题，主持

4.国家自然科学基金委员会，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至2016-12，30万元，结题，主持

5.科学技术部，“一带一路”创新人才交流外国专家项目，DL2023145001L，农情信息智能遥感监测技术海外应用合作开发，2023-01至2024-12，20万元，结题，主持

6.自然资源部，委托研究项目，高光谱卫星遥感在耕地生产力监测与评价中的拓展应用，2019-11至2020-12，45万元，结题，主持

7.江苏省农学会，委托项目，江苏省稻麦种植情况遥感监测，2021-07至2023-12，70万元，结题，主持

8.南京市农业装备推广中心，委托项目，2024年夏季小麦和油菜还田面积卫星遥感监测服务，2024-05至2024-07，19.8万元，结题，主持

9.南京市农业装备推广中心，委托项目，2023年夏季小麦和油菜还田面积卫星遥感监测服务，2023-05至2023-06，20万元，结题，主持

10.南京市农业装备推广中心，委托项目，2022年夏季小麦和油菜种植面积进行遥感检测服务，2022-05至2022-06，20万元，结题，主持

11.中化现代农业有限公司，委托项目，桓台县数字农业农村项目田块边界提取，2022-03至2022-05，9.35万元，结题，主持

12.国家自然科学基金委员会，创新研究群体项目，32021004，粮食作物生产力监测预测机理与方法，2021-01至2025-12，1000万元，资助期满，参加

13.江苏省财政厅，江苏省农业科技自主创新资金项目，CX（21）1006，粮食作物生产力监测预测关键技术与安全预警平台，2021-07至2025-06，220万，结题，第二负责人

14.挪威驻华大使馆，中国-挪威国际合作项目子课题，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至2017-06，34.8万元，结题，主持

15.江苏省信息农业重点实验室，重大自主研究项目，KLIAZZ2301，农情信息天空地高精度监测关键技术与应用平台，2023-1-1至2025-12-31，100万元，在研，主持

16.南京农业大学，中央高校基本科研业务费项目，RENCAI2025028，消除生育期影响的稻瘟病严重度遥感监测，2025-01至2025-12，30万元，在研，主持

17.南京农业大学，中央高校基本科研业务费项目，XUEKEN2023023，10米分辨率全国冬小麦种植区遥感制图技术，2023-01至2023-12，10万元，结题，主持

18.南京农业大学，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至2016-12，25万元，结题，主持

19.南京农业大学，南京农业大学-塔里木大学联合项目，KYLH201603，基于高光谱的南疆灰枣叶片水分状况监测机理研究，2016-01至2018-12，30万元，结题，主持

五、奖励荣誉：

• 科学研究

1.长江学者特聘教授，教育部，2025年

2.全球农情遥感监测关键技术与应用，测绘科学技术奖一等奖（排名5/15），中国测绘学会，2023年

3.神农青年英才，农业农村部，2022年

4.2021年度Remote Sensing of Environment最佳审稿人，2021年

5.神农中华农业科技奖优秀创新团队奖（排名第8），2021年

6.第三届中国作物学会青年科技奖，2019年

7.第四届江苏省青年遥感与地理信息科技奖，2018年

• 教育教学

1.江苏高校外国留学生教学观摩比赛一等奖，江苏省高等教育学会外国留学生教育管理研究委员会，2025年

2.江苏省优秀博士学位论文指导老师，2022年

3.南京农业大学研究生教育“优秀导师团队”（5/7），2022年

4.农学院英才优秀教师奖和突出贡献奖，2020年

5.农学院优秀教师，2017年

6.农学院青年授课比赛一等奖，2016年

六、主要社会兼职：

1.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（2019/05-2029/05）

2.中国农学会农业信息分会副主任委员（2024/01-2029/01）

3.中国植物营养与肥料学会智慧耕肥专委会副主任委员（2025/08-）

4.国际数字地球学会中国国家委员会成像光谱对地观测专业委员会委员（2025/10-2029/10）

5.中国遥感应用协会高光谱遥感技术与应用专业委员会委员（2022/01-2023/08）

6.中国作物学会智慧农业专业委员会理事（2022/01-2027/01）

7.中国农业生物技术学会植物表型组学专业委员会委员（2017/7-2022/7）

8.江苏省遥感与地理信息系统学会常务理事（2020/12-）

9.江苏省人工智能学会智能遥感专业委员会常务委员（2021/4-2025/4）

10.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing副主编（2021/2-）

11.CABI Agriculture & Bioscience副主编（2021/6-）

12.Precision Agriculture编委/副主编（2021/8-）

13.ISPRS International Journal of Geo-information编委（2015/6-2024/2）