Full publication list:
https://scholar.google.com/citations?hl=zh-CN&user=62j-dqgAAAAJ&view_op=list_works&sortby=pubdate
代表性研究成果 (*通讯)
Xu, Y., Ciais, P., Santoro, M., Bourgoin, C., Ritter, F., Pellissier-Tanon, et al. (2026). Small persistent humid forest clearings drive tropical forest biomass losses. Nature, 649(8096), 375–380. https://doi.org/10.1038/s41586-025-09870-7
Su, Y.*, Xu, Y.*, Zhang, X., Makowski, D., et al. (2026). Disturbance characteristics and forest properties regulate surface warming and recovery across Europe. Nature Geoscience, 19(9), 1082–1090. https://doi.org/10.1038/s41561-026-02071-5
Zhou, C., Ciais, P., Mittakola, R. T., Zhu, B., Su, Y., & Xu, Y.* (2026). Global Marine LNG Terminals, Tankers & Trade: A High-Resolution AIS-Based Dataset of LNG Trade (2020–2024). Scientific Data. https://doi.org/10.1038/s41597-026-07454-2
Xu, Y., Yu, L., Ciais, P., Li, W., Santoro, M., Yang, H., & Gong, P. (2022). Recent expansion of oil palm plantations into carbon-rich forests. Nature Sustainability, 5(7), 574–577. https://doi.org/10.1038/s41893-022-00872-1
Xu, Y., Ciais, P., Yu, L., Li, W., Chen, X., Zhang, H., Yue, C., Kanniah, K., Cracknell, A. P., & Gong, P. (2021). Oil palm modelling in the global land surface model ORCHIDEE-MICT. Geoscientific Model Development, 14(7), 4573–4592. https://doi.org/10.5194/gmd-14-4573-2021
Xu, Y., Yu, L., Li, W., Ciais, P., Cheng, Y., & Gong, P. (2020). Annual oil palm plantation maps in Malaysia and Indonesia from 2001 to 2016. Earth System Science Data, (12), 847–867.
Xu, Y., Yu, L., Peng, D., Zhao, J., Cheng, Y., Liu, X., Li, W., Meng, R., Xu, X., & Gong, P. (2020). Annual 30-m land use/land cover maps of China for 1980–2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm. Science China Earth Sciences, 63(9), 1390–1407. https://doi.org/10.1007/s11430-019-9606-4
Xu, Y., Yu, L., Zhao, F. R., Cai, X., Zhao, J., Lu, H., & Gong, P. (2018). Tracking annual cropland changes from 1984 to 2016 using time-series Landsat images with a change-detection and post-classification approach: Experiments from three sites in Africa. Remote Sensing of Environment, 218, 13–31. https://doi.org/10.1016/j.rse.2018.09.008
Xu, Y., Yu, L., Cai, Z., Zhao, J., Peng, D., Li, C., Lu, H., Yu, C., & Gong, P. (2019). Exploring intra-annual variation in cropland classification accuracy using monthly, seasonal, and yearly sample set. International Journal of Remote Sensing, 40(23), 8748–8763. https://doi.org/10.1080/01431161.2019.1620377
Xu, Y., Yu, L., Feng, D., Peng, D., Li, C., Huang, X., Lu, H., & Gong, P. (2019). Comparisons of three recent moderate resolution African land cover datasets: CGLS-LC100, ESA-S2-LC20, and FROM-GLC-Africa30. International Journal of Remote Sensing, 40(16), 6185–6202. https://doi.org/10.1080/01431161.2019.1587207
Xu, Y., Yu, L., Peng, D., Cai, X., Cheng, Y., Zhao, J., Zhao, Y., Feng, D., Hackman, K., Huang, X., Lu, H., Yu, C., & Gong, P. (2018). Exploring the temporal density of Landsat observations for cropland mapping: Experiments from Egypt, Ethiopia, and South Africa. International Journal of Remote Sensing, 39(21), 7328–7349. https://doi.org/10.1080/01431161.2018.1468115
Xu, Y., Yu, L., Zhao, Y., Feng, D., Cheng, Y., Cai, X., & Gong, P. (2017). Monitoring cropland changes along the Nile River in Egypt over past three decades (1984–2015) using remote sensing. International Journal of Remote Sensing, 38(15), 4459–4480. https://doi.org/10.1080/01431161.2017.1323285