April 15, 2020
GERS Lab received a 207K grant from Eversource (PI: Zhe Zhu) that will assess forest risk to infrastructure using satellite time series.
Feburary 1, 2020
Welcome our new GERS member Xiucheng Yang from the University of Strasbourg, France. He will be working on the USGS coastal tidal wetland project.
December 11, 2019
Zhe Zhu is featured in UConn Today
October 21, 2019
GERS Lab received a grant (135K) from the Department of Energy and Environment Protection (PI: Chadwick Rittenhouse; Co-I: Zhe Zhu) to work on the estimation of the young forest and shrubland habitat in Connecticut.
September 16, 2019
GERS Lab received a 350K USGS grant (PI: Zhe Zhu) that will study methods for improving change detection and classification for the USGS LCMAP program.
September 1, 2019
GERS Lab received a 200K USGS grant (PI: Zhe Zhu) that will study coastal tidal wetlands based on satellite time series.
August 1, 2019
Former GERS Lab Postdoctoral Researcher at Texas Tech University Congcong Li joined the LCMAP team at EROS USGS working as the Land Change Scientist. Big Congratulations!
August 1, 2019
Zhe Zhu is the Associate Editor of Science of Remote Sensing
July 5th, 2019
Zhe Zhu joined the Editorial Board of Remote Sensing
June 25th, 2019
GERS Lab (PI: Zhe Zhu) received 116K NASA grant to work on mapping and characterizing human activity changes using NASA Black Marble Product Suite.
May 6th, 2019
GERS Lab received 870K USGS grant between 2019 and 2022 to work on near real-time land change monitoring for the Conterminous US.
January 1st, 2019
GERS Lab has officially moved to the University of Connecticut, Storrs, CT!
June 12th, 2018
Dr. Zhu will give a Webinar for Geoscience and Remote Sensing Society (GRSS) Sponsored by the Washington DC / Northern Virginia Chapter of GRSS on June 12 at 12:00 PM (US Eastern Time). His talk title is “Monitoring Land Change in Near Real-time”. You can find it here.
May 6th, 2018
New book chapter from GERS lab is ready to be downloaded. The first comprehensive review of Landsat cloud and cloud shadow detection. Thanks Shi, Binbin, and Chengbin! You can find it here or at researchgate here. The citation for this book chapter is as follows:
- Zhu, Z., S. Qiu, B. He, C. Deng (2018), Cloud and cloud shadow detection for Landsat images: the fundamental basis for analyzing Landsat time series, In Weng, Q. (Ed.): Remote Sensing Time Series Image Processing (1st ed., pp. 3-24), Boca Raton, FL: CRC Press/Taylor & Francis.
May 4th, 2018
Congratulations to Amal! She has passed her PhD qualify exam and successfully defended her PhD proposal and we can now call her PhD candidate!
April 27th, 2018
New grant received from Climate Corporation working on cotton stress monitoring based on drones and satellite time series.
- Quantifying Cotton Water Stress Using Unmanned Aerials Systems and Satellite Remote Sensing, PI: W. Guo, Co-I: Z. Zhu, The Climate Corp, $130,000, 2018-2019