Dr. ZHANG Miao is an associate professor at the State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences. He earned his Ph.D. in Cartography and Geographical Information System from the University of Chinese Academy of Sciences in 2014. He is a key member of the CropWatch team, which provides remote sensing-based global agricultural monitoring through a cloud platform. As a member of the Executive Committee of the GEOGLAM Flagship and a co-lead of the Joint Experiments for Crop Assessment and Monitoring (JECAM) Initiative, he has collaborated with researchers from over 20 countries and various international organizations within the GEOGLAM framework. His research focuses on remote sensing-based agriculture monitoring, specifically big Earth data for cropland and cropping intensity mapping, crop classification using multi-source remote sensing imagery and crop area estimates, and remote sensing-based agricultural monitoring and food security assessment. Dr. Zhang has authored over 100 scientific papers across various disciplines, including remote sensing, agronomy, water resources, food security, and disaster assessment.

[1] Zhao, H., Wu, B., Zhang, M.*, Long, J., Tian, F., Xie, Y., ... & Li, J. (2025). A large-scale VHR parcel dataset and a novel hierarchical semantic boundary-guided network for agricultural parcel delineation. ISPRS Journal of Photogrammetry and Remote Sensing, 221, 1-19.

[2] Zhang, M.; Bingfang Wu, et al. (2022). GCI30: a global dataset of 30-m cropping intensity using multisource remote sensing imagery, Earth System Science Data, 13(10), 4799-4817. 

[3] Wu, B., Zhang, M., Zeng, H., Tian, F., Potgieter, A. B., Qin, X., ... & Loupian, E. (2023). Challenges and opportunities in remote sensing-based crop monitoring: a review. National Science Review, 10(4), nwac290.

[4] Bofana, J.; Zhang, M.*; Nabil, M.; et al. How long did crops survive from floods caused by Cyclone Idai in Mozambique detected with multi-satellite data. Remote Sensing of Environment, 2022, 269:112808. 

[5] Liu, Chong, Qi Zhang, Shiqi Tao, …, Zhang, Miao*, et al. A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication. Remote Sensing of Environment, 2020, 251:112095.

[6] Mohsen Nabil, Miao Zhang*, José Bofana, et al. Assessing factors impacting the spatial discrepancy of remote sensing based cropland products: A case study in Africa. International Journal of Applied Earth Observation and Geoinformation 2020: 102010.

[7] Zhang Miao, Wu Bingfang, Meng Jihua, 2014. Quantifying winter wheat residue biomass with a spectral angle index derived from China Environmental Satellite data. International Journal of Applied Earth Observation and Geoinformation, 2014，32: 105-113. 

[8] Zhang Miao, Wu Bingfang, Yu Mingzhao, et al., 2014. Crop condition assessment with adjusted NDVI using uncropped arable land ratio, Remote Sensing, 6 (6), 5774-5794.