Huang Wenli
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
School/Department:School of Resource and Environmental Sciences
Administrative Position:Associate Professor
Education Level:With Certificate of Graduation for Doctorate Study
Alma Mater:Wuhan University
Discipline:Cartography and Geoinformation Engineering
Cartography and Geography Information Systems
Honors and Titles
2022 Gold Award of the 12th "Challenge Cup · Bank of China" Undergraduate Entrepreneurship Plan Competition in Hubei Province
2023 Outstanding Instructor of Wuhan University 2022 Undergraduate Extracurricular Academic Science and Technology Innovation and Entrepreneurship Competition
2022 Gold Award of Innovation Group of China Youth Innovation and Entrepreneurship Competition (Digital Economy Special) (Instructor)
2014 Ann G. Wylie Dissertation Fellowship
2012 Goldhabor International Travel Grant
2006 Excellent undergraduate of Wuhan University
Hits:
Duration of Study:2021-2024
Employment Status:浙江省测绘科学研究院
Major:地图制图学与地理信息工程
Research Focus:遥感数据辐射质量改善
Education Level:Under postgraduate
Degree:Master's degree
Current Status:Studying
Graduation Thesis Title:面向多源国产高分影像的季度无缝植被指数产品生成方法研究
Student ID:2021202050079
Date of Registration:2021-09-01
Date of Graduation:2024-06-28
Wenli Huang is an Associate Professor at Wuhan University. From 2015 to 2018, she worked as a Post-doc Research Associate with the Department of Geographical Sciences at the University of Maryland, College Park where she completed her Ph.D. in 2015. She received a B.S. from Wuhan University in 2006, and M.S. from the Beijing Normal University in 2009.
Her current areas of interest cover important land cover components, including forest and water.
Wenli's primary research is aimed at creating a better understanding of terrestrial forest ecosystems. She is interested in measuring the tree canopy cover and carbon stocks stored in forest areas using lidar, optical/radar remote sensing, and field data. Also, she is actively involved in developing automated approaches for monitoring the inundated area using optical and radar remote sensing data.
