Ying Tu

About

Ying Tu is a Postdoctoral Associate in the Department of Global Development at Cornell University. She specializes in remote sensing, geospatial analysis, and quantitative methodologies. Her research focuses on harnessing satellite remote sensing and computational approaches to monitor global environmental changes in support of sustainable development. Specifically, she is interested in large-scale land cover/land use mapping, agricultural sustainability, human development, and environmental justice. Currently, Ying's research is centered on assessing the suitability of rice farming in agricultural flood plains of New York State and its ecosystem benefits.

Prior to joining Cornell, Ying earned her Ph.D. in Ecology from Tsinghua University in 2024. Her doctoral work concentrated on monitoring high-resolution cropland dynamics in China and examining its relationship with urbanization. From 2022 to 2023, she served as a Research Assistant at the University of Hong Kong, where she developed a broad interest in human-environment interactions. Her research ranged from evaluating the widespread effects of the Olympic Games on urban greenspaces to assessing the impact of the Russia-Ukraine conflict on agricultural production in eastern Ukraine. She completed her B.S. in Geographical Information Science at Sun Yat-sen University in 2019.

Publications

• Tu, Y., Wu, S., Chen, B., Weng, Q., Bai, Y., Yang, J., ... & Xu, B. (2024). A 30 m annual cropland dataset of China from 1986 to 2021. Earth System Science Data, 16(5), 2297-2316.
• Tu, Y., Chen, B., Yang, J., & Xu, B. (2023). Olympic effects on reshaping urban greenspace of host cities. Landscape and Urban Planning, 230, 104615.
• Tu, Y., Chen, B., Yu, L., Song, Y., Wu, S., Li, M., ... & Xu, B. (2023). Raveling the nexus between urban expansion and cropland loss in China. Landscape Ecology, 38(7), 1869-1884.
• Tu, Y., Chen, B., Yu, L., Xin, Q., Gong, P., & Xu, B. (2021). How does urban expansion interact with cropland loss? A comparison of 14 Chinese cities from 1980 to 2015. Landscape Ecology, 36, 243-263.
• Tu, Y., Chen, B., Lang, W., Chen, T., Li, M., Zhang, T., & Xu, B. (2021). Uncovering the Nature of Urban Land Use Composition Using Multi-source Open Big Data with Ensemble Learning. Remote Sensing, 13(21), 4241.
• Tu, Y., Chen, B., Zhang, T., & Xu, B. (2020). Regional Mapping of Essential Urban Land Use Categories in China: A Segmentation-Based Approach. Remote Sensing, 12(7), 1058.
• Tu, Y., Lang, W., Yu, L., Li, Y., Jiang, J., Qin, Y., ... & Xu, B. (2020). Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5384-5397.
• Tu, Y., Zhou, H., Lang, W., Chen, T., Li, X., & Xu, B. (2020). A novel cross-sensor calibration method to generate a consistent night-time lights time series dataset. International Journal of Remote Sensing, 41(14), 5482-5502.

Education

• Ph.D. in Ecology, Tsinghua University
• B.S. in Geographic Information Science, Sun Yat-sen University