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DTSTART;TZID=America/New_York:20250611T103000
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DESCRIPTION:Spanning over 30% of the planet’s landmass\, the global fores
 ts play significant roles in local and global ecosystems as well as planet
 ary systems including the global carbon cycle. One of the fundamental tech
 nical challenges of any new space-borne vegetation remote sensing mission 
 is the determination of what sensor(s) to place on-board and what\, if any
 \, overlapping modes of operation they will employ as each on-board sensor
  adds significant cost to the overall mission. In this thesis\, the streng
 ths of various remote sensing technologies are explored in the context of 
 measuring forest parameters through the fusion of different remote sensing
  technologies. Polarimetric radar\, LiDAR\, and near-IR passive optical se
 nsing platforms are employed in conjunction with physics-based models. It 
 is shown that this proposed method can achieve high accuracy estimates whi
 le using minimal ancillary data in the estimation process. It is further s
 hown that this method can be extended to regions lacking a full-suite of r
 emotely sensed measurements. Transitioning from sensor fusion to the effec
 t of phenomenology on SAR and InSAR\, this thesis presents a novel approac
 h to accurately gauge the impact of the wind\, a temporal decorrelator\, o
 n these two technologies.\n\nSpeaker(s): Michael Benson\n\nRoom: 3316\, Bl
 dg: EECS\, 1301 Beal Ave\, Ann Arbor\, Michigan\, United States\, 48109-21
 22
LOCATION:Room: 3316\, Bldg: EECS\, 1301 Beal Ave\, Ann Arbor\, Michigan\, U
 nited States\, 48109-2122
ORGANIZER:lep@umich.edu
SEQUENCE:13
SUMMARY:Multimodal Remote Sensing of Complex Forests for Height and Biomass
  Estimation
URL;VALUE=URI:https://events.vtools.ieee.org/m/488466
X-ALT-DESC:Description: <br /><p>Spanning over 30% of the planet&rsquo\;s l
 andmass\, the global forests play significant roles in local and global ec
 osystems as well as planetary systems including the global carbon cycle. O
 ne of the fundamental technical challenges of any new space-borne vegetati
 on remote sensing mission is the determination of what sensor(s) to place 
 on-board and what\, if any\, overlapping modes of operation they will empl
 oy as each on-board sensor adds significant cost to the overall mission. I
 n this thesis\, the strengths of various remote sensing technologies are e
 xplored in the context of measuring forest parameters through the fusion o
 f different remote sensing technologies. Polarimetric radar\, LiDAR\, and 
 near-IR passive optical sensing platforms are employed in conjunction with
  physics-based models.&nbsp\; It is shown that this proposed method can ac
 hieve high accuracy estimates while using minimal ancillary data in the es
 timation process. It is further shown that this method can be extended to 
 regions lacking a full-suite of remotely sensed measurements. Transitionin
 g from sensor fusion to the effect of phenomenology on SAR and InSAR\, thi
 s thesis presents a novel approach to accurately gauge the impact of the w
 ind\, a temporal decorrelator\, on these two technologies.</p>
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