个人简历

教育背景
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
工作履历
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

研究领域

1. 城市及生态环境遥感监测
2. 全球城市空间扩张及可持续评价
3. 全球土地利用模拟及预测
4. 植被物候监测及模型研究
5. 城市能源使用及气候变化响应""

近期论文

2021年:
1. Shi, C., Qu, L.Q., Zhang, W.Q., Li, X.C. 2021. A systematic review on sloping farmland use based on a perspective of bibliometric analysis. Agricultural Water Management, 244, 106564. doi: 10.1016/j.agwat.2020.106564.
2020年:
1. Zhang, J., Yu, L., Li, X.C., Zhang, C.C., Shi, T.Z., Wu, X.Y., Yang, C., Gao, W.X., Li, Q.Q., Wu, G.F. 2020. Exploring annual urban expansions in Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal features and driving factors in 1986-2017. Remote Sensing, 12(16), 2516. doi:10.3390/rs12162615.
2. Hackman, K.O., Li, X.C., Gyambibi, D.A., Asamoach, E.A., & Nelson, I.D. 2020. Analysis of geo-spatiotemporal data using machine algorithms and reliability enhancement for urbanization decision support. International Journal of Digital Earth. 1-16. doi: 10.1080/17538947.2020.1805036.
3. Weber, M., Hao, D.L., Asrar, G.R., Zhou, Y., Li, X.C., & Chen, M. 2020. Exploring the use of DSCOVR/EPIC satellite observations to monitor vegetation phenology. Remote Sensing, 12, 2384. doi: 10.3390/rs12152384.
4. Zhao, J.Y., Yu, L., Xu, Y.D., Li, X.C., Liu, H., Huang, X.M., Wang, D., Ren, C., & Gong, P. 2020. Exploring differences in land surface temperature between the city centers and urban expansion areas of China’s major cities. International Journal of Remote Sensing, 41, 8963-8983. doi: 10.1080/01431161.2020.1797216.
5. Zhao, M., Zhou, Y.Y., Li, X.C., Cheng, W.M., Zhou, C.H., Ma, T., Li, M.C., & Huang, K. 2020. Mapping urban dynamics (1992-2018) in Southeast Asia using fused nighttime light data from DMSP and VIIRS. Remote Sensing of Environment. doi: 10.1016/j.res.2020.111980.
6. Hu, T.Y., Li, X.C., Gong, P., Yu, W.C., & Huang, X.C. 2020. Evaluating the effect of plain afforestation project and future spatial suitability in Beijing. China Science: Earth Science, 63. doi: 10.1007/s11430-019-9636-0.
7. Sapkota, A., Dong, Y., Li, L.Z., Asrar, G., Zhou, Y.Y., Li, X.C., Coates, F., Spanier, A.J., Matz, J., Bielory, L., Breitenother, A.G., Mitchell, C.,& Jiang, C.S. 2020. Association Between Changes in Timing of Spring Onset and Asthma Hospitalization in Maryland. JAMA Network Open, 3, e207551. doi: 10.1001/jamanetworkopen.2020.7551.
8. 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.
9. 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.
10. 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.
11. 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.
12. Liu, X., Zhou, Y.Y., Yue, W.Z., Li, X.C., Liu, Y., & Lu, D.B. 2020. Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature. Journal of Cleaner Production, 257, 120529. doi: 10.1016/j.jclepro.2020.120529.
13. 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.
14. 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.
15. Meng, L., Mao, J.M., Zhou, Y.Y., Richardson, A.D., Lee, X.H., Thornton, P.E., Ricciuto, D.M., Li, X.C., Dai, Y.J., Shi, X.Y., & Jia, G.S. 2020. Urban warming advances spring phenology but reduces temperature response of plants in the conterminous United States. 2020. Proceedings of the National Academy of Sciences of the United States of America, 117, 4228-4233. doi:10.1073/pnas.1911117117.
16. Cao, W.T., Zhou, Y.Y., Li, R., & Li, X.C. 2020. Mapping changes in coastlines and tidal flats in developing islands using the full time series of Landsat images. Remote Sensing of Environment, 239, 1-11. doi: 10.1016/j.res.2020.111665.
17. Meng, L., Zhou, Y.Y., Li, X.C., Asrar, G.R., Mao, J.F., Wanamaker, A.D., & Wang, Y.Q. 2020. Divergent responses of spring phenology to daytime and nighttime warming. Agricultural and Forest Meteorology, 281, 107832. doi: 10.1016/j.agrformet.2019.107832
18. 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.
19. Gong, P., Chen, B., Li, X.C., Liu, H., Wang, J., Bai, Y.Q., Chen, J.M., Chen, X., Feng, S.L., Huang, H.B., Huang, X.C., Jie, Y.W., Kang, Y.D., Lei, G.B., Li, A.N, Li, X.T., Li, X., Li, Y.C., Li, Z.L., Li, Z.D., Liu, C., Liu, C.X., Liu, M.C., Liu, S.G., Mao, W.L., Miao., C.H., Ni, H., Suen, H.P., Sun, B., Sun, F.D., Sun, J., Sun, L., Tian. T., Tong, X.H., Tseng, Y.S., Tu, Y., Wang, H., Wang, L., Wang, X., Wang, Z.M., Wu, T.H., Yang, J., Yue, W.Z., Zeng, H.D., Zhang, K., Zhang, N., Zhang, T., Zhang, Y., Zhao, F., Zheng, Y.C., Zhou, Q.M., Clinton, N., Zhu, Z.L., & Xu, B. 2020. Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018. Science Bulletin, 65, 182-187. doi: 10.1016/j-sclb.2019.12.007.
2019年:
1. Wei, J.Z., Zheng, K., Zhang, F., Fang, C., Zhou, Y.Y., Li, X.C., & Li, F.M. 2019. Migration of rural residents to urban areas drives grassland vegetation increase in China's Loess Plateau. Sustainability, 11(23), 6764. doi:10.3390/su11236764.
2. Zhao, M., Zhou, Y.Y., Li, X.C., Zhou, C.H., Cheng, W.M., & Li, M.C. 2019. Building a series of consistent night-time light data (1992-2018) in southeast Asia by integrating DMSP-OLS and NPP VIIRS. IEEE Transactions on Geoscience and Remote Sensing, 1-14. doi: 10.1109/TGRS.2019.2949797.
3. Zhao, M., Zhou, Y.Y., Li, X.C., Cao, W.T., He, C.Y., Yu, B.L., Li, X., Elvidge, C., Cheng, W.M., & Zhou, C.H. 2019. Applications of satellite remote sensing of nighttime light observations: advances, challenges, and perspectives. Remote Sensing, 11(17), 1971. doi: 10.3390/rs11171971.
4. 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.
5. Wu, Q.S., Lane, C.R., Li, X.C., Zhao, K.G., Zhou, Y.Y., Clinton, N., DeVries, B., Golden, H.E., & Lang, M.W. 2019. Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine. Remote Sensing of Environment, 228, 1-13. doi: 10.1016/j.rse.2019.04.015.
6. 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.
7. 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.
8. 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:
1. 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.
2. Yu, L., Xu, Y.D., Xue, Y.M., Li, X.C., Cheng, Y.Q., Liu, X.X., Porwal, A., Holden, E.J., Yang, Y., & Gong, P. 2018. Monitoring surface mining belts using multiple remote sensing datasets: A global perspective. Ore Geology Reviews, 101, 675-687. doi: 10.1016/j.oregeorev.2018.08.019.
3. 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.
4. Lyu, H.B., Lu, H., Mou, L.C., Li, W.Y., Wright, J., Li, X.C., Li, X.L., Zhu, X.X., Wang, J., Yu, L., & Gong, P. 2018. Long-Term Annual Mapping of Four Cities on Different Continents by Applying a Deep Information Learning Method to Landsat Data. Remote Sensing, 10(3), 471. doi: 10.3390/rs10030471.
2017年:
1. 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.
2. 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.
3. 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.
4. Li, X.M., Zhou, Y.Y., Asrar, G.R., Imhoff, M, & Li, X.C. 2017. The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States. Science of the Total Environment, 605, 426-435. doi: 10.1016/j.scitotenv.2017.06.229.
5. 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.
6. Liang, L., Li, X.C., Huang, Y.B., Qin, Y.C., & Huang, H.B. 2017. Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance. Ecological Modeling, 354, 1-10. doi: 10.1016/j.ecolmodel.2017.03.007.
7. Li, C.C., Gong, P., Wang, J., Zhu, Z.L., Biging, G.S., Yuan, C., Hu, T.Y., Zhang, H.Y., Wang, Q., Li, X.C., Liu, X.X., Xu, Y.D., Guo, J., Liu, C.X., Heckman, K., Zhang, M.N., Cheng, Y.Q., Yu, L., & Yang, J. 2017. The first all-season sample set for mapping global land cover with Landsat-8 data. Science Bulletin, 62(7), 508-515. doi: 10.1016/j.scib.2017.03.011.
8. Reynolds, R., Liang, L., Li, X.C., & Dennis, J. 2017. Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record. Remote Sensing, 9(1), 71. doi:10.3390/rs9010071.
9. 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.
10. Yu, L., Li, X.C., Li, C.C., Zhao, Y.Y., Niu, Z.G., Huang, H.B., Wang, J., Cheng, Y.Q., Si, Y.L., Yu, C.Q., Fu, H.H., & Gong, P. 2017. Using a global reference sample set and a cropland map for area estimation in China. Science China: Earth Science, 60, 277-285. doi:10.1007/s11430-016-0064-5.
11. 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:
1. Zhong, L.H., Yu, L., Li, X.C., Hu, L.N., & Gong, P. 2016. Rapid corn and soybean mapping in US Corn Belt and neighboring areas. Scientific Reports, 6, 36240. doi:10.1038/srep36240.
2. 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.
3. 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.
4. 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.
5. Li, X.C. & Gong, P. 2016. Urban growth models: progress and perspective. Science Bulletin, 61, 1637-1650. doi:10.1007/s11434-016-1111-1.
6. Liang, L., Hawbaker, T.J., Zhu, Z.L., Li, X.C., & Gong, P. 2016. Forest disturbance interactions and successional pathways in the Southern Rocky Mountains. Forest Ecology and Management, 375, 35-45. doi: 10.1016/j.foreco.2016.05.010.
7. Gong, P., Yu, L., Li, C.C., Wang, J., Lu, Liang., Li, X.C., Ji, L.Y., Bai, Y.Q., Cheng, Y.Q., & Zhu, Z.L. 2016. A new research paradigm for global land cover mapping. Annals of GIS, 22(2), 87-102. doi: 10.1080/19475683.2016.1164247.
8. 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.
9. Chen, H., Yu, C., Li, C.S., Xin, Q.C., Huang, X., Zhang, J., Yue, Y.L., Huang, G.R, Li, X.C. & Wang, W. 2016. Modeling the impacts of water and fertilizer management on the ecosystem service of rice rotated cropping systems in China. Agriculture, Ecosystems and Environment, 219, 49-57. doi: 10.1016/j.agee.2015.11.023.
2015年:
1. 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.
2. 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:
1. Yu, L., Wang, J, Zhao, Y.Y., Cheng, Q., Hu, L. Y., Liu, S., Yu, L., Wang, X.Y., Zhu, P., Li, X.Y., Xu, Y., Li, C.C., Fu, W., Li, X.C., Li, W.Y., Liu, C.X., Cong, N., Zhang, H., Sun, F.D., Bi, X.F., Xin, Q.C., Li, D.D., Yan, D.H., Zhu, Z.L., Goodchild, M., & Gong. P. 2014. Meta-discoveries from a synthesis of satellite-based land-cover mapping research. International Journal of Remote Sensing, 35(13), 4573-4588. doi: 10.1080/01431161.2014.930206.
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.
3. 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.
4. Yu, L., Wang, J., Li, X.C., Li, C.C., Zhao, Y.Y., & Gong, P. 2014. A multi-resolution global land cover dataset through multisource data aggregation. Science China: Earth Science, 57(10), 2317-2329. doi:10.1007/s11430-014-4919-z.
5. Yu, C., Li, C.S., Xin, Q.C., Chen, H., Zhang, J., Zhang, F., Li, X.C., Clinton, N., Huang, X., Yue, Y.L & Gong, P. 2014. Dynamic assessment of the impact of drought on agricultural yield and scale-dependent return periods over large geographic regions. Environmental Modeling & Software, 62, 454-464. doi: 10.1016/j.envsoft.2014.08.004.
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.