殷大萌

殷大萌

职　　称

助理研究员

电　　话

电子邮件

yindameng@caas.cn

创新团队

作物栽培与生理

研究组

作物表型

研究中心

作物栽培与耕作中心

教育经历

2021 博士地理学美国纽约州立大学布法罗分校
2013 硕士遥感北京师范大学
2010 学士物理学北京师范大学

工作经历

2020至今助理研究员中国农业科学院作物科学研究所

研究方向

作物表型监测
农业遥感
无人机
激光雷达

学术兼职

美国地理学家协会（AAG）遥感专业组（RSSG）理事
国际华人地理信息科学协会（CPGIS）学生竞赛委员会，理事
Plant Phenomics期刊青年编委

荣誉称号

作物科学研究所2023年度阿里巴巴育种科研人才奖励计划青年科学家
2024 AAG RSSG Early Career Award

承担项目

国家自然科学基金委青年项目：基于LiDAR提取植株三维参数的玉米关键生育时期精准监测，42301427，2024.01-2026.12，30万元，项目负责人
三亚中国农业科学院国家南繁研究院“南繁专项”一般项目：结合多源遥感数据的玉米生育时期精准监测研究，YBXM2305，2023.05-2024.12，50万元，项目负责人
新一代人工智能国家科技重大专项（子课题）：作物群体穗位智能采集设备研制，2022ZD0115701，2022.12-2025.11，72.68万元，子课题负责人
国家重点研发计划（子课题）：表型组产量性状精准鉴定和光周期反应特性鉴定，2021YFD1201602，2021.12-2024.11，380万元，子课题负责人

主要论文

Yin, D., Wang, L., Lu, Y., & Shi, C. (2024). Mangrove tree height growth monitoring from multi-temporal UAV-LiDAR. Remote Sens. Environ. 303, 114002.下载
Yu, X.#, Yin, D.#, Xu, H., Pinto Espinosa, F., Schmidhalter, U., Nie, C., ... & Jin, X. (2024). Maize tassel number and tasseling stage monitoring based on near-ground and UAV RGB images by improved YoloV8. Precis. Agric. 1-39.下载
Jia, X.#, Yin, D.#, Bai, Y., Yu, X., Song, Y., Cheng, M., ... & Jin, X. (2023). Monitoring Maize Leaf Spot Disease Using Multi-Source UAV Imagery. Drones, 7(11), 650.下载

Meng, L.#, Yin, D.#, Cheng, M., Liu, S., Bai, Y., Liu, Y., ... & Jin, X. (2023). Improved Crop Biomass Algorithm with Piecewise Function (iCBA-PF) for Maize Using Multi-Source UAV Data. Drones, 7(4), 254.下载
Bai, T., Wang, L., Yin, D.M., Sun, K., Chen, Y., Li, W., & Li, D. (2023). Deep learning for change detection in remote sensing: a review. Geo-Spat. Inf. Sci. 26(3), 262-288. 【GSIS Excellent Paper Award】下载
Yu, X.#, Yin, D.#, Nie, C., Ming, B., Xu, H., Liu, Y., Bai, Y., Shao, M., Cheng, M., Liu, Y., Liu, S., Wang, Z., Wang, S., Shi, L.*, & Jin, X.* (2022). Maize tassel area dynamic monitoring based on near-ground and UAV RGB images by U-Net model. Comput. Electron. Agric. 203, 107477.下载
Chen, H., Yin, D.*, Chen, J., & Chen, Y. (2022). Automatic Spectral Representation with Improved Stacked Spectral Feature Space Patch (ISSFSP) for CNN-Based Hyperspectral Image Classification. IEEE Trans. Geosci. Remote Sens. 60, 1-14.下载
Liu, S., Yin, D., Feng, H., Li, Z., Xu, X., Shi, L., & Jin, X.* (2022). Estimating maize seedling number with UAV RGB images and advanced image processing methods. Precis. Agric. 1-29.下载
Chen, H., Qiu, Y., Yin, D., Chen, J.*, Chen, X., Liu, S., & Liu, L. (2022). Stacked spectral feature space patch: An advanced spectral representation for precise crop classification based on convolutional neural network. Crop J. 10, 1460-1469.下载
Dong, Q., Chen, X.*, Chen, J., Yin, D., Zhang, C., Xu, F., Rao, Y., Shen, M., Chen, Y., & Stein, A. (2022). Bias of area counted from sub-pixel map: Origin and correction. Sci. Remote Sens. 6, 100069.下载
Yin, D.M., Wang, L.*, Zhu, Z., Clark, S.S., Cao, Y., Besek, J., & Dai, N. (2021). Water quality related to Conservation Reserve Program (CRP) and cropland areas: Evidence from multi-temporal remote sensing. Int. J. Appl. Earth Obs. Geoinf. 96, 102272.下载
Schunder, T., Yin, D.*, Bagchi-Sen, S., & Rajan, K. (2020). A spatial analysis of the development potential of rooftop and community solar energy. Remote Sens. Appl.: Soc. Environ. 19, 100355.下载
Wang, L.*, Diao, C., Xian, G., Yin, D.M., Lu, Y., Zou, S., & Erickson, T.A. (2020). A summary of the special issue on remote sensing of land change science with Google Earth Engine. Remote Sens. Environ. 248, 112002.下载
Yin, D., & Wang, L.* (2019). Individual mangrove tree measurement using UAV-based LiDAR data: possibilities and challenges. Remote Sens. Environ. 223, 34-49. 【ESI高被引】下载
Wang, L.*, Jia, M., Yin, D., & Tian, J. (2019). A review of remote sensing for mangrove forests: 1956-2018. Remote Sens. Environ. 231, 111223. 【ESI高被引】下载
Yin, D., & Wang, L.* (2016). How to assess the accuracy of the individual tree-based forest inventory derived from remotely sensed data: a review. Int. J. Remote Sens. 37(19), 4521-4553.下载
Chen, X., Yin, D., Chen, J.*, & Cao, X. (2016). Effect of training strategy for positive and unlabeled learning classification: test on Landsat Imagery. Remote Sens. Lett. 7(11), 1063-1072.下载
Wang, L.*, Shi, C., Diao, C., Ji, W., & Yin, D.M. (2016). A survey of methods incorporating spatial information in image classification and spectral unmixing. Int. J. Remote Sens. 37(16), 3870-3910.下载
Yin, D., Cao, X., Chen, X., Shao, Y., & Chen, J. (2013). Comparison of automatic thresholding methods for snow-cover mapping using Landsat TM imagery. Int. J. Remote Sens. 34(19), 6529-6538.下载

主要著作

Wang, L.*, Yin, D., Tian, J., & Lu, Y. (2021). Google Earth Engine Advancing Urban Land Change Science. Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment, 175-188.
Wang, L.*, & Yin, D. (2017). Patch metrics. International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology, 1-4.