M
Michelle Hofton
Researcher at University of Maryland, College Park
Publications - 74
Citations - 6779
Michelle Hofton is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Lidar & Elevation. The author has an hindex of 33, co-authored 70 publications receiving 5391 citations. Previous affiliations of Michelle Hofton include Scripps Institution of Oceanography & Goddard Space Flight Center.
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Journal ArticleDOI
Estimation of tropical forest structural characteristics using large-footprint lidar
Jason B. Drake,Ralph Dubayah,David B. Clark,Robert G. Knox,J. Bryan Blair,Michelle Hofton,Robin L. Chazdon,John F. Weishampel,Stephen D. Prince +8 more
TL;DR: In this article, a large-footprint airborne scanning lidar was used to recover forest structural characteristics across a spectrum of land cover types from pasture to secondary and primary tropical forests.
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The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography
TL;DR: The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter designed and developed at NASA's Goddard Space Flight Center as mentioned in this paper, which produces topographic maps with decimeter accuracy and vertical height and structure measurements of vegetation.
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The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography
Ralph Dubayah,J. B. Blair,Scott J. Goetz,Lola Fatoyinbo,Matthew C. Hansen,Sean P. Healey,Michelle Hofton,George C. Hurtt,James R. Kellner,Scott B. Luthcke,John Armston,Hao Tang,Laura Duncanson,Steven Hancock,Patrick Jantz,S. Marselis,Paul L. Patterson,Wenlu Qi,Carlos A. Silva +18 more
TL;DR: The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6° N & S latitude as mentioned in this paper.
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Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy
TL;DR: In this paper, the authors compare estimates of forest structural metrics derived from remote sensing to measurements obtained in the field, and statistically combine structural information from LiDAR, RaDAR and passive optical sensors in an attempt to improve accuracy of their estimates.
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Decomposition of laser altimeter waveforms
TL;DR: The authors develop a method to decompose a laser altimeter return waveform into a series of components assuming that the position of each component within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint.