My current research mainly focuses on the irrigation in land surface models, participating in the sub-project B05 ‘Towards a dynamic representation of irrigation in land surface models’ in the ‘CRC1502 Regional Climate Change: Disentangling the Role of Land Use and Water Management - 2022 to 2025’ project.
Our main task is to better quantify differences in water use between dry and wet years by considering differences in the irrigated area and the irrigated crops in land surface models. The understanding of the dynamics in irrigation processes will be improved, and the comprehensively quantification human influences on water and energy flows will be carried out.
Previous work is mainly about the application of remote sensing in agriculture, including crop phenotyping using multi-source UAV remote sensing data; optimization of UAV monitoring schemes for crop growth, such as design optimal UAV sensor combinations and UAV flight mission schemes; diagnosis of environmental stresses of crop growth via the integration of UAV and satellite remote sensing.
Yang B, Zhu W, Eyshi Rezaei E, et al. The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing, Remote Sensing, 2022, 14(7): 1559
Zhu W, Eyshi Rezaei E, Nouri H, et al. Quick detection of field-scale soil comprehensive attributes via the integration of UAV and Sentinel-2B remote sensing data, Remote Sensing, 2021, 13(22): 4716
Zhu K, Sun Z, Zhao F, Yang T, Tian Z, Lai J, Zhu W, Long B. Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress. Remote Sensing 2021, 13, 250.
Zhu W, Sun Z, Huang Y, et al. Optimization of multi-source UAV RS agro-monitoring schemes designed for field-scale crop phenotyping, Precision Agriculture, 2021, 22(02).
Zhu W, Sun Z, Li B, et al. Analysis of Spatial Heterogeneity for Soil Attributes and Spectral Indices-based Diagnosis of Coastal Saline-Alkaline Farmland Stress Using UAV Remote Sensing, Journal of Geo-information Science, 2021, 23(03), 536-549. (In Chinese with English abstract)
Zhu W, Sun Z, Yang T, et al. Estimating leaf chlorophyll content of crops based on a comprehensive framework for UAV remote sensing monitoring, Computers and Electronics in Agriculture, 2020, 178, 105786.
Zhu W, Sun Z, Huang Y, et al. Improving field-scale crop LAI retrievals based on UAV remote sensing observations and optimized VI-LUT, Remote Sensing, 2019, 11(20), 2456.
Zhu W, Sun Z, Peng J, et al. Estimating Maize Above-ground Biomass using 3D point clouds of multi-source UAV data at multi-spatial scales, Remote Sensing, 2019, 11(22), 2678.
Zhu W, Huang Y, Sun Z. Mapping Crop Leaf Area Index from Multi-Spectral Imagery Onboard an Unmanned Aerial Vehicle, in: 2018 7th International Conference on Agro-Geoinformatics. IEEE, Hangzhou, 2018, pp. 1–5.
Zhu W, Li S, Zhang X, et al. Estimation of winter wheat yield using optimal vegetation indices from unmanned aerial vehicle remote sensing, Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(11):78-86. (In Chinese with English abstract)
Research Gate: https://www.researchgate.net/profile/Wanxue_Zhu
Google scholar: https://scholar.google.com/citations?user=eXGPKx8AAAAJ&hl=en