北京师范大学全球变化与地球系统科学研究院

当前位置：首页»科学研究» 科研动态【06.12讲座】Understanding Compound Disturbances in Forests with Multi-sensor Remote Sensing 发布时间：Wed Jun 01 17:55:00 CST 2016

主题：Understanding Compound Disturbances in Forests with Multi-sensor Remote Sensing

时间：2016年06月12日(星期日)14:00-16:00

地点：京师科技大厦B座520,学院南路12号

主讲人：Dr. Gang Chen

讲座内容介绍：

The world's forests absorb as much as 30% of annual anthropogenic carbon dioxide emissions. However, the ability of forest ecosystems to capture atmospheric carbon is increasingly affected by a variety of disturbances. Although almost none of those disturbances are new, a growing number of studies confirmed that their intensities and frequencies have substantially increased over the past decades. It becomes more common that a forest experiences compound disturbances at the same time. This talk presents several case studies that employ multi-sensor remote sensing to better understand the specific role of individual disturbances across forests in both the natural and urban environments.

主讲人简介:

Dr. Chen is an Assistant Professor in the Department of Geography and Earth Sciences at the University of North Carolina at Charlotte, USA. His research focuses on the application of multi-sensor remote sensing to monitor the change of our terrestrial ecosystems and understand how natural (e.g., climate change, fire, and plant disease) and anthropogenic factors (e.g., urban development, and the construction of hydroelectric dams) drive the change. He has been working on a variety of projects, across several regions/countries including Antarctica, Brazil, Canada, China, Myanmar, Thailand, Turkey, and the United States. Dr. Chen serves on the editorial board of the ISPRS Journal of Photogrammetry and Remote Sensing, the official journal of the international largest remote sensing society ISPRS. He received the 2016 Early Career Scholar in Remote Sensing Award from the American Association of Geographers, 2015 Junior Faculty Development Award from UNC Charlotte, 2014 North Carolina Space Grant New Investigators Program Award, and 2011 National Best Ph.D. Thesis Award from the Canadian Remote Sensing Society.