DONG Yingying: Associate Professor, working in Aerospace Information Research Institute, Chinese Academy of Sciences, Ph.D. The main research areas include remote sensing inversion mechanisms and models of crop physical and chemical parameters, monitoring and early warning mechanisms and methods for the development dynamics of pests and diseases, and the development of an intelligent platform for crop growth and disease monitoring and forecasting.

[1] Li Xiaowen Remote Sensing Application Award, 2025

[2] Beijing Science and Technology Progress Award, Second Prize, 2023

[3] GEO Team Impact Award, 2023

[4] China Remote Sensing Outstanding Achievement Award, Second Prize, 2023

[5] High-Resolution Application Achievement Award, First Prize, 2023

[6] Invention, Entrepreneurship, and Innovation Award, Second Prize, 2023

[7] Surveying and Mapping Science and Technology Progress Award, First Prize, 2023

[8] DaBeinong Science and Technology Innovation Award, 2022

[9] Liang Xi Forestry Science and Technology Progress Award, Second Prize, 2021

[1] Yingying Dong, Longlong Zhao, Wenjiang Huang. < Monitoring of Desert Locust in Africa and Asia>, Science Press, Springer, Beijing, 2023.01. ISBN: 978-981-19-7238-6.

[2] Yingying Dong, Wenjiang Huang, Yun Geng, Linyi Liu, Huiqin Ma, Anting Guo and Chao Ruan, <Crop Pest and Disease Remote Sensing Monitoring and Forecasting>, Science Press, EDP Sciences, 2022.03. ISBN: 978-2-7598-2659-9.

[3] Guo, J., Huang, W., Dong, Y., Lin, K., Yue, F., Shan, Y., ... & Ding, X. (2025). A weight-adaptive updated method for grasshopper habitat mapping at the national scale using remote sensing: Combined with spatial heterogeneity and landscape. ISPRS Journal of Photogrammetry and Remote Sensing, 227, 84-98.

[4] Yingying Dong, Fang Xu, Linyi Liu, et al. Automatic System for Crop Pest and Disease Dynamic Monitoring and Early Forecasting[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 4410-4418.

[5] Qi T, Dong Y, Li X L, et al. Fall armyworm habitat analysis in Africa with multi-source earth observation data[J]. Computers and Electronics in Agriculture, 2024, 225: 109283.

[6] Guo J, Huang W, Dong Y, et al. Spatiotemporal monitoring of grasshopper habitats using multi-source data: Combined with landscape and spatial heterogeneity[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 130: 103838.

[7] Han Y, Dong Y, Zhu Y, et al. Remote sensing inversion of vegetation parameters with IPROSAIL-Net[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023.

[8] Zhao M, Dong Y, Huang W, et al. Regional-Scale Monitoring of Wheat Stripe Rust Using Remote Sensing and Geographical Detectors[J]. Remote Sensing, 2023, 15(18): 4631.

[9] Huang L, Chen X, Dong Y, et al. Dynamic Analysis of Regional Wheat Stripe Rust Environmental Suitability in China[J]. Remote Sensing, 2023, 15(8): 2021.

[10] Wang J, Huang Y, Huang L, et al. Migration risk of fall armyworm (Spodoptera frugiperda) from North Africa to Southern Europe[J]. Frontiers in Plant Science, 2023, 14: 1141470.

[11] Xueling Li, Yingying Dong*, Yining Zhu, et al. Enhanced Leaf Area Index Estimation with CROP-DualGAN Network[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, DOI: 10.1109/TGRS.2022.3230354.

[12] Yingxin Xiao, Yingying Dong*, Wenjiang Huang, et al. Regional prediction of Fusarium head blight occurrence in wheat with remote sensing based Susceptible-Exposed-Infectious-Removed model[J]. International Journal of Applied Earth Observations and Geoinformation, 2022, 114: 103043.

[13] Ruiqi Sun, Wenjiang Huang, Yingying Dong*, et al. Dynamic Forecast of Desert Locust Presence Using Machine Learning with a Multivariate Time Lag Sliding Window Technique[J]. Remote Sensing, 2022, 14(3): 747-767.