芦俊俊，男，汉族，1988年生，中共党员。博士毕业于中国农业大学，中国科学院地理所博士后，河南理工大学讲师。主要从事农业3S应用、精准农业、农田氮素循环方面的研究，2017年短期访问并参加欧洲精准农业大会，2021年获国际农业地理信息学年青科学家优秀奖。主讲《GIS原理与应用》、《水土保持学》、《空间信息基础与前沿》等课程。

科研项目：

1. 参与中国农业大学资源与环境学院张福锁教授主持的国家重点基础研究发展计划项目“作物高产高效群体与关键生态因子的匹配及其调控”

2. 参与十三五重点研发计划项目课题二“基于传感器的变量施肥关键技术与装备”

3. 参与中国农业大学主持的中挪项目Innovative technologies to assure sustainable grain production in China with reduced environmental footprint与中英项目Remote Sensing for Sustainable Intensification in China through Improved Farm Decision-Making

4. 主持河南省教育厅项目一项、科技厅项目一项

论文情况：

1. Lu, J., Dai, E., Miao, Y., Kusnierek, K., 2022. Improving active canopy sensor-based in-season rice nitrogen status diagnosis and recommendation using multi-source data fusion with machine learning. Journal of Cleaner Production 380, 134926. （SCI收录，JCR 1区）

2. Lu, J., Wang, H., Miao, Y., Zhao, L., Zhao, G., Cao, Q., Kusnierek, K., 2022. Developing an active canopy sensor-based integrated precision rice management system for improving grain yield and quality, nitrogen use efficiency, and lodging resistance. Remote Sensing 14, 2440. （SCI收录，JCR 1区）

3. Lu, J., Miao, Y., Shi, W., Li, J., Hu, X., Chen, Z., Wang, X., Kusnierek, K., 2020. Developing a proximal active canopy sensor-based precision nitrogen management strategy for high-yielding rice. Remote Sensing 12, 1440. （SCI收录，JCR 1区）

4. Lu, J., Miao, Y., Shi, W., Li, J., Yuan, F. 2017. Evaluating different approaches to non-destructive nitrogen status diagnosis of rice using portable RapidSCAN active canopy sensor. Scientific Reports 7, 14073. (SCI收录, JCR 2区)

5. Lu, J., Miao, Y., Shi, W., Li, J., Wan, J., Gao, X., Zhang, J., Zha, H. 2017. Using portable RapidSCAN active canopy sensor for rice nitrogen status diagnosis. Advances in Animal Biosciences: Precision Agriculture (ECPA) 8, 349-352.

6. Lu, J., Miao, Y., Huang, Y., Shi, W. 2016. In-season diagnosis of rice nitrogen status using Crop Circle sensor and UAV remote sensing. Proceedings of the 13th International Conference on Precision Agriculture. July 31 –Aug. 3, 2016. St. Louis, Missouri, USA.

7. Lu, J., Miao, Y., Huang, Y., Shi, W., Hu, X., Wang, X., Wan, J. 2015. Evaluating an unmanned aerial vehicle-based remote sensing system for estimation of rice nitrogen status. In Proceedings of Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics 2015), July 19-24, 2015. Istanbul, Turkey. pp. 198-203. (EI收录)

8. Lu, J., Miao, Y., Shen, J., Cao, Q., Huang, S., Wang, H., Wu, H., Hu, S., Hu, H. 2015. Improving estimation of rice yield potential using active canopy sensor Crop Circle ACS 430 in Northeast China. In J. V. Stafford (ed.) Precision Agriculture'15, Wageningen Academic Publishers, pp. 102-115. (EI收录)

9. Shi, W.*, Lu, J.*, Miao, Y., Cao, Q., Shen, J., Wang, H., Hu, H., Hu, S., Yang, W., Li, H. 2015. Evaluating a Crop Circle active canopy sensor-based precision nitrogen management strategy for rice in Northeast China. In Proceedings of Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics 2015), July 19-24, 2015. Istanbul, Turkey. pp. 261-264. (共同第一作者，EI收录)

10. Chen, Z., Miao, Y., Lu, J., Zhou, L., Li, Y., Zhang, H., Lou, W., Zhang, Z., Kusnierek, K., Liu, C. 2019. In-Season diagnosis of winter wheat nitrogen status in smallholder farmer fields across a village using unmanned aerial vehicle-based remote sensing. Agronomy 9, 619. (SCI收录)

11. Zhang, J., Miao, Y., Batchelor, W., Lu, J., Wang, H., Kang, S. 2018. Improving High-Latitude Rice Nitrogen Management with the CERES-Rice Crop Model. Agronomy, 2018, 8, 263. (SCI收录)

12. Shi, W., Miao, Y., Cao, Q., Lu, J., Shen, J., Yu, W., Wang, H. 2016. A precision nitrogen management strategy combining slow release fertilizer and in-season active canopy sensing for rice in Northeast China. Proceedings of the 13th International Conference on Precision Agriculture. July 31 –Aug. 3, 2016. St. Louis, Missouri, USA.

13. Wang, X., Miao, Y., Guan, Y., Xia, T., Lu, J., Mulla, D., 2016. An evaluation of two active canopy sensor systems for non-destructive estimation of spring maize biomass. In Proceedings of the 5th International Conference on Agro-geoinformatics (Agro-geoinformatics 2016), July 18-20, 2016. Tianjin, China. (EI收录)