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DTSTART:20220313T030000
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DTSTART:20221106T010000
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DTSTAMP:20221103T172754Z
UID:C718FDCC-C189-4917-AB5D-708385537D9F
DTSTART;TZID=America/New_York:20221102T153000
DTEND;TZID=America/New_York:20221102T163000
DESCRIPTION:Salehi-Geolab led by Dr Bahram Salehi at SUNY is an active rese
 arch lab with multiple PhD\, MSc\, and BSc students conducting research in
  monitoring the environment at various scales from national level to state
 \, regional and landscape levels. We combine multi-sensor space borne synt
 hetic aperture radar (SAR)\, multispectral\, and lidar as well use unmanne
 d aerial vehicle (UAV) data through advanced machine/deep learning to stud
 y various ecosystems. In this talk\, I will present a quick summary of our
  research and findings in three primary areas including nation-wide wetlan
 d monitoring\, state-wide forest biomass and carbon\, inland freshwater wa
 ter quality monitoring\, and detailed 3D forest modelling using satellite\
 , airborne and UAV-based earth observation data. Our project areas include
  regions in the U.S\, Canada\, and Latin America.\n\nSpeaker(s): Bahram Sa
 lehi\, \n\nBldg: 76\, Center for Image Science\, 54 Lomb Memorial Drive\, 
 Rochester\, New York\, United States\, 14623\, Virtual: https://events.vto
 ols.ieee.org/m/330661
LOCATION:Bldg: 76\, Center for Image Science\, 54 Lomb Memorial Drive\, Roc
 hester\, New York\, United States\, 14623\, Virtual: https://events.vtools
 .ieee.org/m/330661
ORGANIZER:emmett@cis.rit.edu
SEQUENCE:4
SUMMARY:Advanced Remote Sensing Technologies for Environmental Monitoring
URL;VALUE=URI:https://events.vtools.ieee.org/m/330661
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Salehi-Geolab led by Dr Bahram Salehi at S
 UNY is an active research lab with multiple PhD\, MSc\, and BSc students c
 onducting research in monitoring the environment at various scales from na
 tional level to state\, regional and landscape levels. We combine multi-se
 nsor space borne synthetic aperture radar (SAR)\, multispectral\, and lida
 r as well use unmanned aerial vehicle (UAV) data through advanced machine/
 deep learning to study various ecosystems. In this talk\, I will present a
  quick summary of our research and findings in three primary areas includi
 ng nation-wide wetland monitoring\, state-wide forest biomass and carbon\,
  inland freshwater water quality monitoring\, and detailed 3D forest model
 ling using satellite\, airborne and UAV-based earth observation data. Our 
 project areas include regions in the U.S\, Canada\, and Latin America.&lt;/p&gt;
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