Tuesday, June 12, 2018
4:00 PM GMT/UTC
12:00 PM US Eastern Daylight Time
Speaker: Zhe Zhu, Texas Tech University
Sponsored by the Washington DC / Northern Virginia Chapter of GRSS
Want to learn more about monitoring Land Change in Near Real-Time?Attend here (Meeting Number: 595 681 439, Meeting Password: 9ThWXi7Z).
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Land change science has emerged as one of the most important components for research in global environmental change and sustainability. This interdisciplinary field seeks to understand the dynamics of land cover and land use as a coupled human-environment system, in which one of the essential components is to observe and monitor different land changes. This talk will introduce an algorithm called Continuous Change Detection and Classification (CCDC) that has the capability of monitoring land change in near real-time and at the same time characterizing the land cover before and after the change. Algorithm improvement and current applications of the CCDC algorithm, and future directions of near real-time monitoring of land changes will also be discussed.
SPEAKER’S BIO:
Zhe Zhu is currently an assistant Professor of Geography at Texas Tech University. He obtained a B.E. in Remote Sensing and Photogrammetry from Wuhan University (China) in 2006, and a Ph.D. degree in Geography from Boston University in 2013.
His research interests include remote sensing of cloud, urban, and forest, time series analysis, change detection, land cover/land use mapping, near real-time monitoring, and climate change. He has have published more than 20 peer-reviewed papers in top remote sensing journals. He has been a Principal, Co-Principal Investigator, or Collaborator on 7 grants from USGS, NASA, and Private Corporation (~$9 M).
Recently, he is selected as the USGS-NASA Landsat Science Team Member (2018-2023) and EROS CalVal Center of Excellence Science Interface Panel (2018-2021). He is also the Associate Editor of Remote Sensing of Environment, the Associate Editor of Arabian Journal of Geosciences, and on the Editorial Board of PeerJ. Details are available at: www.myweb.ttu.edu/zhezhu/
