李雪草

2008.09-2012.07 中山大学 地理信息系统系 本科 理学学士

2012.09-2016.03 清华大学 地球系统科学系 理学博士

2016.04-2020.06  艾奥瓦州立大学 地质和大气系 博士后

2020.10-              中国农业大学 土地科学与技术学院 教授

 《All Earth》副主编 (2021-至今)

《Earth System Science Data》专题编辑 (2022-至今)

《Remote Sensing》编委 (2021-至今)

《Journal of Remote Sensing》等客座编辑

《Remote Sensing》《Land》客座编辑

国家科技部科技评估中心专家

1. 城市及生态环境遥感监测

2. 全球土地利用模拟及预测

3. 农用地作物分布遥感制图

4. 农业生态系统可持续评价

课题组网站：https://www.x-mol.com/groups/li_xuecao

1. 清华大学-浪潮集团计算地球科学青年人才奖 (2023)

2. 地理信息科技进步奖一等奖 (2022)

3. 自然资源部卫星海洋环境动力学国家重点实验室(SOED)“青年访问海星学者” (2022)

4. 国家级高层次青年人才 (2021)

5. 中国农业大学高层次“杰出人才”计划(2020)

6. 清华大学优秀博士论文一等奖(2016)

1. 国家级高层次青年人才项目 (2022-2025)

2. 中国农业大学高层次“杰出人才”引进项目(2021-2025)

3. 国家自然科学基金青年项目(2022-2024)

4. 教育部高等教育司产学合作协同育人项目(2023-2023)

5. 国家自然科学基金面上项目(2024-2027)

 一、发表论文

 2023年:

49. Yin, P.Y., Li, X.C.*, Zhou, Y.Y., Mao, J.F., Fu, Y.S., Cao, W.T., Gong, P., He, W.R., Li, B.G., Huang, J.X., Liu, X.P., Shi, Z.T., Liu, D.L., Guo, J.C. 2023. Urbanization effects on the spatial patterns of spring vegetation phenology depend on the climatic background. Agricultural and Forest Meteorology. doi: accept.

48. Yuan, B., Li, X.C.*, Zhou, L., Bai, T.C., Hu, T.Y., Huang, J.X., Liu, D.L., Li, Y.C., Guo, J.C. 2023. Global distinct variations of surface urban heat islands in inter- and intra-cities revealed by local climate zones and seamless daily land surface temperature data. ISPRS Journal of Photogrammetry and Remote Sensing, 204, 1-14. doi: 10.1016/j.isprsjprs.2023.08.012.

47. Geng, M.Q., Li, X.C.*, Mu, H.W., Yu, G.J., Chai, L., Yang, Z.W., Liu, H.M., Huang, J.X., Liu, H., Ju, Z.S. 2023. Human footprints in the Global South accelerate biomass carbon loss in ecologically sensitive regions. Global Change Biology. doi: 10.1111/GCB.16900s.

46. He, W.R., Li, X.C.*, Zhou, Y.Y.*, Shi, Z.T., Yu, G.J., Hu, T.Y., Wang, Y.X., Huang, J.X., Bai, T.C., Sun, Z.C., Liu, X.P., Gong, P. 2023. Global urban fractional changes at a 1km resolution throughout 2100 under eight scenarios of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Earth System Science Data, 15(8), 3623-3639. doi: 10.5194/essd-15-3623-2023.

45. Wang, Y.X., Li, X.C.*, Yin, P.Y., Yu, G.J., Cao, W.T., Liu, J.X., Pei, L., Hu, T.Y., Zhou, Y.Y., Liu, X.P., Huang, J.X., Gong, P. 2023. Characterizing annual dynamics of urban form at the horizontal and vertical dimensions using long-term Landsat time series data. ISPRS Journal of Photogrammetry and Remote Sensing, 203, 199-210. doi: 10.1016/j.isprsjprs.2023.07.025.

44. Shi, Z.T., Li, X.C.*, Hu, T.Y., Yuan, B., Yin, P.Y., Jiang, D.B. 2023. Modeling the intensity of surface urban heat island based on the impervious surface area. Urban Climate, 49, 101529. doi: 10.1016/j.uclim.2023.101529.

43. He, W.R., Li, X.C.*, Zhou, Y.Y., Liu, X.P., Gong, P., Hu, T.Y., Yin, P.Y., Huang, J.X., Yang, J.Y., Miao, S.X., Wang, X., Wu, T.H. 2023. Modeling gridded urban fractional change using the temporal context information in the urban cellular automata model. Cities, 133, 104146. doi: 10.1016/j.cities.2022.104146.

42. Yin, P.Y., Li, X.C.*, Mao, J.F., Johnson, B.A., Wang, B.Y., Huang, J.X. 2023. A comprehensive analysis of the crop effect on the urban-rural differences in land surface phenology. Science of the Total Environment, 160604. doi: 10.1016/j.scitotenv.2022.160604.

41. Lin, F.Q. *#, Li, X.C. #, Jia, N.Y. #, Feng, F., Huang, H., Huang, J.X., Fan, S.G., Ciais, P., Song, X.P. 2023. The impacts of Russia-Ukraine conflict on global food security. Global Food Security, 36, 100661. doi: 10.1016/j.gfs.2022.100661.

2022年:

40. Zhou, Y.Y. #*, Li, X.C.#, Chen, W., Meng, L., Wu, Q.S., Gong, P., Seto, K.C. 2022. Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South. Proceedings of the National Academy of Sciences of the United States of America, 119(46), e2214813119. doi: 10.1073/pnas.2214813119.

39. Mu, H.W., Li, X.C.*, Zhou, Y.Y., Gong, P., Huang, J.X., Du, X.P., Guo, J.C., Cao, W.T., Sun, Z.C., Xu, C., Liu, D.L.*. Identifying discrepant regions in urban mapping from historical and projected global urban extents. All Earth, 34(1), 167-178. doi: 10.1080/27669645.2022.2104990.

38. Wen, Y.N., Li, X.C.*, Mu, H.W., Zhong, L.H., Chen, H., Zeng, Y.L., Miao, S.X., Su, W., Gong, P., Li, B.G., Huang, J.X.*. 2022. Mapping corn dynamics using limited but representative samples with adaptive strategies. ISPRS Journal of Photogrammetry and Remote Sensing, 190, 252-266. doi: 10.1016/j.isprsjprs.2022.06.012.

37. Li, L.Z., Li, X.C.*, Asrar, G., Zhou, Y.Y., Chen, M., Zeng, Y.L., Li, X.J., Li, F., Luo, M., Sapkota, A., Hao, D.L.*. 2022.  Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State. International Journal of Applied Earth Observations and Geoinformation, 110, 102815. doi: 10.1016/j.jag.2022.102815.

36. Li, X.C., Zhou, Y.Y.*, Gong, P. 2022. Diversity in global urban sprawl patterns revealed by Zipfian dynamics. Remote Sensing Letters, 1-11. doi: 10.1080/2150704X.2022.2073794.

35. Yu, G.J., Xie, Z.X., Li, X.C.*, Wang, Y.X., Huang, J.X., Yao, X.C. 2022. The Potential of 3-D Building Height Data to Characterize Socioeconomic Activities: A Case Study from 38 Cities in China. Remote Sensing, 14, 2087. doi: 10.3390/rs14092087.

34. Mu, H.W., Li, X.C.*, Wen, Y.N., Huang, J.X., Du, P.J., Su, W., Miao, S.X., Geng, M.Q. 2022. A global record of annual terrestrial Human Footprint dataset from 2000 to 2018. Scientific Data, 9, 176. doi: 10.1038/s41597-022-01284-8. [Highly Cited Paper]

33. Mu, H.W., Li, X.C.*, Ma, H.J., Du, X.P., Huang, J.X., Su, W., Zhen, Y., Xu, C., Liu, H.L., Yin, D.Q, Li, B.G. 2022. Evaluation of the policy-driven ecological network in the Three-North Shelterbelt region of China. Landscape and Urban Planning, 218, 104305. doi: 10.1016/j.landurbplan.2021.104305. [Highly Cited Paper]

32. Zhang, Y.H., Yin, P.Y., Li, X.C.*, Niu, Q.D., Wang, Y.X., Cao, W.T., Huang, J.X., Chen, H., Yao, X.C., Yu, L., Li, B.G. 2022. The divergent response of vegetation phenology to urbanization: A case study of Beijing city, China. Science of the Total Environment, 803, 150079. doi: 10.1016/j.scitotenv.2021.150079.

 2021年:

31. Li, X.C., Zhou, Y.Y.*, Hejazi, M., Wise, M., Vernon, C., Iyer, G., Chen, W. 2021. Global urban growth between 1870 and 2100 from integrated high resolution mapped data and urban dynamic modelling. Communication Earth & Environment, 2(1), 201. doi: 10.1038/s43247-021-00273-w.

30. Li, X.C.*, Zhang, J., Li, Z.Y., Hu, T.Y., Wu, Q.S., Zhao, Y.Y., Yang, J., Huang, J.X., Zhou, Y.Y., Liu, X.P., Gong, P, & Wang, X. 2021. The critical role of temporal contexts in evaluating urban cellular automata models. GIScience & Remote Sensing. doi:10.1080/15481603.2021.1946261.

29. Mu, H.W., Li, X.C.*, Du, X.P., Huang, J.X., Su, W., Hu, T.Y., Wen, Y.N., Yin, P.Y., Han, Y., & Xue, F. 2021. Evaluation of light pollution in global protected areas from 1992 to 2018. Remote Sensing, 13(9): 1849. doi: 10.3390/rs13091849.

 2020年:

28. Li, X.C., Gong, P., Zhou, Y.Y., Wang, J., Bai, Y.Q., Chen, B., Hu, T.Y., Xiao, Y.X., Xu, B., Yang, J., Liu, X.P., Cai, W.J., Huang, H.B., Wu, T.H., Wang, X., Lin, P., Li, X., Chen, J., He, C.Y., Li, X., Yu, L., Clinton, N., & Zhu, Z.L. 2020. Mapping global urban boundaries from the global artificial impervious area (GAIA) data. Environmental Research Letters, 15, 094044. doi: 10.1088/1748-9326/ab9be3. [Highly Cited Paper]

27. Li, X.C., Zhou, Y.Y, Zhao, M., & Zhao, X. 2020. A harmonized global nighttime light dataset 1992-2018. Scientific Data, 7, 168. doi: 10.1038/s41597-020-0510-y. [Highly Cited Paper]

26. Li, X.C., Zhou, Y.Y., & Chen, W. 2020. An improved urban cellular automata model by using the trend adjusted neighborhood. Ecological Processes, 9, 28. doi: 10.1186/s13717-020-00234-9.

25. Liu, X.P., Huang, Y.H., Xu, X.C., Li, X.C., Li, X., Ciasi, P., Gong, K., Ziegler, A.D., Chen, A.P., Gong, P., Chen, J., Hu, G.H., Chen, Y.M., Wang, S.J., Wu, Q.S., Huang, K.N., Estes, L., & Zeng, Z.Z. 2020. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nature Sustainability, doi: 10.1038/s41893-020-0521-x. [Highly Cited Paper]

24. Li, X.C., Zhou, Y.Y., Gong, P., Seto, K.C., & Clinton, N. 2020. Developing a method to estimate building height from Sentinel-1 data. Remote Sensing of Environment, 240, 111705. doi: 10.1016/j.res.2020.111705.

23. Li, X.C., Zhou, Y.Y., Zhu, Z.Y., & Cao, W.T. 2020. A national dataset of 30-m annual urban extent dynamics (1985–2015) in the conterminous United States. Earth System Science Data, 12, 357-371. doi: https://doi.org/10.5194/essd-12-357-2020.

22. Gong, P., Li, X.C., Wang, J., Bai, Y., Chen, B., Hu, T.Y., Liu, X.P., Xu, B., Yang, J., Zhang, W., & Zhou, Y.Y. 2020. Annual maps of global artificial impervious areas (GAIA) between 1985 and 2018. Remote Sensing of Environment, 236, 111510. doi: 10.1016/j.rse.2019.111510. [Highly Cited Paper] [Hot Paper]

2019年:

21. Li, X.C., Zhou, Y.Y., Meng, L., Asrar, G., Lu, C.Q., & Wu, Q.S. 2019. A dataset of 30-meter annual vegetation phenology indicators (1985-2015) in urban areas of the conterminous Unites States. Earth System Science Data, 11(2), 881-894. doi:10.5194/essd-11-881-2019.

20. Li, X.C., Zhou, Y.Y., Eom, J.Y., Yu, S., & Asrar, G.R. 2019. Projecting global urban area growth through 2100 based on historical time-series data and future Shared Socioeconomic Pathways. Earth’s Future, 7(4), 351-362. doi:10.1029/2019EF001152.

19. Gong, P., Li, X.C., & Zhang, W. 2019. 40-year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing. Science Bulletin, 64, 756-763. doi: 10.1016/j.scib.2019.04.024. [Highly Cited Paper] [Hot Paper]

18. Li, X.C., Zhou, Y.Y., Meng, L., Asrar, G.R., Sapkota, A., & Coates, F. 2019. Characterizing the relationship between satellite phenology and pollen season: a case study of birch. Remote Sensing of Environment, 222,269-274. doi: 10.1016/j.rse.2018.12.036.

2018年:

17. Zhou, Y.Y., Li, X.C., Asrar, G.R., Smith, S.J., & Imhoff, M. 2018. A global record of annual urban dynamics (1992-2013) from nighttime lights. Remote Sensing of Environment, 219, 206-220. doi: 10.1016/j.rse.2018.10.015. [Highly Cited Paper] 

16. Li, X.C., Zhou, Y.Y., Zhu, Z.Y., Liang, L., Yu, B.L, & Cao, W.T. 2018. Mapping annual urban dynamics (1985-2015) using time series of Landsat data. Remote Sensing of Environment, 216, 674-683. doi: 10.1016/j.rse.2018.07.030.

2017年:

15. Li, X.C., Lu, H., Zhou, Y.Y., Hu, T.Y., Liang, L., Liu, X.P., Hu, G.H., & Yu, L. 2017. Exploring the performance of spatio-temporal assimilation in an urban cellular automata model. International Journal of Geographic Information Science., 31(11), 2195-2215. doi: 10.1080/13658816.2017.1357821.

14. Li, X.C., Gong, P., Yu, L., & Hu, T.Y. 2017. A segment derived patch-based logistic cellular automata for urban growth modeling with heuristic rules. Computers, Environment & Urban Systems, 65, 140-149. doi: 10.1016/j.compenvurbsys.2017.06.001.

13. Li, X.C., Zhou, Y.Y., Asrar, G.R., & Meng, L. 2017. Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data. Science of the Total Environment. 605, 721-734. doi: 10.1016/j.scitotenv.2017.06.245.

12. Li, X.C., & Y.Y. Zhou. 2017. A Stepwise Calibration of Global DMSP/OLS Stable Nighttime Light Data (1992–2013). Remote Sensing, 9(6), 637. doi:10.3390/rs9060637.

11. Li, X.C., & Zhou, Y.Y. 2017. Urban mapping using DMSP/OLS stable night-time light: a review. International Journal of Remote Sensing, 38(21), 6030-6046. doi:10.1080/01431161.2016.1274451. [Highly Cited Paper] 

10. Li, X.C., Zhou, Y.Y., Asrar, G., Mao, J.F., Li, X.M., & Li, W.Y., 2017. Response of vegetation phenology to urbanization in the conterminous United States. Global Change Biology, 23(7), 2818-2830. doi:10.1111/gcb.13562.

2016年:

9. Li, X.C. & Gong, P. 2016. An “exclusion-inclusion” framework for extracting human settlements in rapidly developing regions of China from Landsat images. Remote Sensing of Environment, 188, 286-296. doi:10.1016/j.rse.2016.08.029.

8. Li, X.C., Yu L., Xu, Y.D., Yang, J., & Gong. P. 2016. Ten years after Hurricane Katrina: monitoring recovery in New Orleans and the surrounding areas using remote sensing. Science Bulletin, 61, 1460-1470. doi:10.1007/s11434-016-1167-y.

7. Li, X.C., Le, Y., Sohl, T., Clinton, N., Li, W.Y., Zhu, Z.L., Liu, X.P., & Gong, P. 2016. A cellular automata downscaling based 1 km global land use datasets (2010–2100). Science Bulletin, 61, 1651-1661. doi:10.1007/s11434-016-1148-1.

6. Li, X.C. & Gong, P. 2016. Urban growth models: progress and perspective. Science Bulletin, 61, 1637-1650. doi:10.1007/s11434-016-1111-1.

5. Hu, T.Y., Yang, J., Li, X.C., & Gong, P. 2016. Mapping urban land use by using Landsat images and open social data. Remote Sensing, 8(2), 151. doi:10.3390/rs8020151. [Highly Cited Paper] 

2015年:

4. Li, X.C., Gong, P. & Lu, Liang. 2015. A 30-year (1984–2013) record of annual urban dynamics of Beijing City derived from Landsat data. Remote Sensing of Environment, 166, 78-90. doi: 10.1016/j.rse.2015.06.007. [Highly Cited Paper] 

3. Li, X.C., Liu, X.P. & Gong, P. 2015. Integrating ensemble-urban cellular automata model with an uncertainty map to improve the performance of a single model. International Journal of Geographical Information Science, 29, 762-785. doi: 10.1080/13658816.2014.997237.

2014年:

2. Li, X.C., Liu, X.P. & Yu, L. 2014. A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules. International Journal of Geographical Information Science, 28(7), 1317-1335. doi: 10.1080/13658816.2014.883079.

1. Li, X.C., Liu, X.P. & Yu, L. 2014. Aggregative model-based classifier ensemble for improving land-use/cover classification of Landsat TM Images. International Journal of Remote Sensing, 35(4), 1481-1495. doi: 10.1080/01431161.2013.878061.

二、出版著作：

1．“一带一路”非洲东北部区生态环境遥感监测. 北京:科学出版社, 2019, 参编.