李桂英教授

发布者:孙杰 发布时间:2018-10-08 浏览次数:31

------------------------------------------------------------------------------------------------------

基本信息 Basic information

    名:李桂英

    称:教授

硕导/博导:

最高学位:博士

行政职务:

其它兼职:

    位:福建师范大学地理科学学院

------------------------------------------------------------------------------------------------------

联系方式 Contact

通讯地址:

邮政编码:350007

办公电话:0591-83465214    

电子邮箱:ligy326@yahoo.com

------------------------------------------------------------------------------------------------------

研究方向 Research Interests

土地利用和土地覆盖及其变化,遥感,GIS,农业土地生产力和适用性研究,城市人口估测,生活质量评价。

------------------------------------------------------------------------------------------------------

个人履历 Resume

教  育

2003.08-2008.05美国 印第安纳州立大学 地理学 博士

2002.01-2003.07  美国 印第安纳州立大学 地理学 硕士

1989.08-1992.07  南京林业大学 林学专业 硕士

1985.09-1989.07  南京林业大学 林学专业 学士

工  作

1992.07-1998.08  中国林业科学院亚热带林业研究所 助理研究员;

2003.01-2005.12  美国印第安纳州立大学地理系 研究助理;

2006.08-2009.12  美国奥本大学林业和野生动物科学院 副研究员;

2010.01-2014.06  美国印第安纳大学全球环境变化研究中心 博士后;

2014.07-2016.09  美国密歇根州立大学全球变化与对地观测研究中心 副研究员;

2016.10-2018.08  浙江农林大学环境与资源学院 教授;

2018.11至今     福建师范大学地理科学学院  教授

-------------------------------------------------------------------------------------------------------

个人简介  Brief

李桂英,女19697生,教授,硕士生导师,福建师范大学地理科学学院教授2008毕业于美国印第安纳州立大学,获地理学博士学位,2010在美国印第安纳大学从事遥感博士后研究先后在美国奥本大学、密歇根州立大学全球变化观测中心工作,副研究员2016回国,20189至今在福建师范大学地理科学学院任职。

2005以来在《ISPRS Journal of Photogrammetry and Remote Sensing》等国际刊物发表32SCI论文,其中以第一作者通讯作者发表9SCI论文先后担任ISPRS Journal of Photogrammetry and Remote Sensing、《IEEE Journal of Selected Topics in Earth Observation and Remote SensingEnvironment Management》等8遥感/地理信息系统期刊的审稿专家。

-------------------------------------------------------------------------------------------------------

代表性论文 Selected Publications

  1. Li, G., Lu, D., Moran, E., Calvi, M.F., Dutra, L.V., and Batistella, M., 2018. Examining deforestation and agropasture dynamics along the Brazilian TransAmazon highway using multitemporal Landsat imagery. GIScience & Remote Sensing. https://doi.org/10.1080/15481603.2018.1497438.

  2. Guo, W., Li, G., Ni, W., Zhang, Y., and Lu, D. 2018. Exploring improvement of impervious surface estimation at national scale through integration of nighttime light and Proba-V data. GIScience & Remote Sensing. 55(05), 698-716, doi: 10.1080/15481603.2018.1436425.

  3. Li, G., Messina, J.P., Peter, B.G., and Sieglinde, S.S. 2017. Mapping land suitability for agriculture in Malawi. Land Degradation and Development. 28: 2001–2016. doi: 10.1002/ldr.2723.

  4. Lu, D., Li. G., and Moran, E. 2014. Current situation and needs of change detection techniques. International Journal of Image and Data Fusion.  doi.org/10.1080/19479832.2013.868372.

  5. Li, G., Lu, D., Moran, E., and Hetrick, S., 2013. Mapping impervious surface area in the Brazilian Amazon using Landsat imagery. GIScience & Remote Sensing, 50 (2), 172-183.  

  6. Li, G., Lu, D., Moran, E., and Sant’Anna, S.J.S., 2012. A comparative analysis of classification algorithms and multiple sensor data for land use/land cover classification in the Brazilian Amazon. Journal of Applied Remote Sensing, 6 (1), 061706 (Dec 14, 2012).

  7. Li, G., Lu, D., Moran, E., Dutra, L., and Batistella, M., 2012. A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. ISPRS Journal of Photogrammetry and Remote Sensing, 70, 26-38.

  8. Li, G., Lu, D., Moran, E., and Hetrick, S., 2011. Land-cover Classification in a Moist Tropical Region of Brazil with Landsat TM Imagery. International Journal of Remote Sensing. 32(23), 8207-8230, DOI:10.1080/01431161.2010.532831.

  9. Li, G. and Weng, Q., 2010. Fine-Scale Population Estimation: How Landsat ETM+ Imagery Can Improve Population Distribution Mapping? Canadian Journal of Remote Sensing, 36 (3), 166-184.

  10. Li, G. and Weng, Q., 2007. Measuring the quality of life in city of Indianapolis by the integration of remote sensing and census data, International Journal of Remote Sensing, 28, 249-267.

  11. Li, G. and Weng, Q., 2005. Using Landsat ETM+ imagery to measure population density in Indianapolis, Indiana, USA, Photogrammetric Engineering & Remote Sensing, 71(8), 947-958.

-------------------------------------------------------------------------------------------------------

主要获奖成果 The Main Achievements

-------------------------------------------------------------------------------------------------------

科研项目 Research projects

……